Federal Job Classification: Comparison of Job Content with Grades
Assigned in Selected Occupations (Letter Report, 10/95, GAO/GGD-96-20).

Pursuant to a congressional request, GAO reviewed the relationship
between job content and General Schedule (GS) grades assigned using the
Factor Evaluation System (FES), focusing on whether the relationship
varied on the basis of the proportion of women and minorities in various
occupations.

GAO found that: (1) the difference between actual GS grades and the
grades based on job content under FES was directly related to female and
minority representation in nonsupervisory positions reviewed; (2) the
likelihood of a position being overgraded increased as the incumbents'
GS grades increased, but there was no correlation between undergrading
and GS grades; (3) occupations with high female representation were more
likely to be undergraded than those occupations with medium or low
female representation; (4) occupations with high minority representation
were more likely to be overgraded than those occupations with medium or
low minority representation; (5) classification experts believed that
FES did not place sufficient value on the physical demands and working
conditions of certain specialist occupations with high minority
representation, which caused them to be overgraded on a strict FES
basis; (6) private sector wage levels may have resulted in overgraded
positions in computer-related occupations; (7) the Office of Personnel
Management (OPM) needs to monitor its development of a new federal job
classification system to ensure that disparities are identified and
addressed; and (8) OPM has established a new oversight office which will
conduct a governmentwide classification study.

--------------------------- Indexing Terms -----------------------------

 REPORTNUM:  GGD-96-20
     TITLE:  Federal Job Classification: Comparison of Job Content with 
             Grades Assigned in Selected Occupations
      DATE:  10/95
   SUBJECT:  Federal employees
             GS grade classification
             Women
             Minorities
             Statistical methods
             Personnel management
             Surveys
             Job classification
IDENTIFIER:  Factor Evaluation System
             General Schedule System
             
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Cover
================================================================ COVER


Report to Congressional Requesters

November 1995

FEDERAL JOB CLASSIFICATION -
COMPARISON OF JOB CONTENT WITH
GRADES ASSIGNED IN SELECTED
OCCUPATIONS

GAO/GGD-96-20

Federal Job Classification

(966406)


Abbreviations
=============================================================== ABBREV

  CPDF - Central Personnel Data File
  FES - Factor Evaluation System
  GS - General Schedule
  MSPB - Merit System Protection Board
  OPM - Office of Personnel Management
  PATCO - Professional, Administrative, Technical, Clerical, Other

Letter
=============================================================== LETTER


B-217675

November 6, 1995

The Honorable John Glenn
Ranking Minority Member
Committee on Governmental Affairs
United States Senate

The Honorable William L.  Clay
House of Representatives

The Honorable Eleanor Holmes Norton
House of Representatives

The Honorable Vic Fazio
House of Representatives

The Honorable Steny H.  Hoyer
House of Representatives

Over the years, many studies have suggested that women and minorities
are paid less than men and nonminorities who work in comparable
positions.  These observations have raised questions about whether
the federal government's classification systems result in lower
grades being assigned to positions in occupations having large
numbers of female or minority incumbents than to other comparable
occupations.  This report responds to your request that we determine
whether the relationship between job content and grades assigned
using the Factor Evaluation System (FES) varied on the basis of the
proportions of women and minorities in occupations.\1


--------------------
\1 FES, which covers almost one-third of the federal full-time
permanent white-collar workforce, is a point-factor system for
determining grades and is considered to be more orderly or rigorous
than other federal classification systems. 


   BACKGROUND
------------------------------------------------------------ Letter :1

Position classification systems are formal methods for determining
the relative worth of positions in an organization.  The Office of
Personnel Management (OPM) has responsibility and authority for
federal position classification, except for certain positions in
agencies exempted by law.  OPM develops and issues classification
standards and policies for the federal personnel system.  Federal
agencies then use these standards and policies to assign grades to
positions. 

The General Schedule (GS) is a 15-grade pay system that covers 442
white-collar occupations and approximately 1.5 million full-time
permanent employees in the federal white-collar workforce.  Agencies
classify most of these positions using either narrative or FES
point-factor classification standards.\2 The FES primary standard
serves as the framework for individual classification standards
written for each occupation.  When we began our study, FES standards
were in effect for 77 occupations covering approximately 441,000
full-time permanent nonsupervisory employees. 

Under FES, positions are assigned grades on the basis of the duties,
responsibilities, and the qualifications required in terms of the
following nine factors: 

  knowledge required by the position includes the skills needed to
     apply that knowledge;

  supervisory controls entail the control exercised by the
     incumbent's supervisor (not the incumbent's span of control over
     subordinates);

  guidelines provide reference data or impose certain constraints on
     the incumbent's use of knowledge; include desk manuals,
     established procedures and policies, traditional practices, and
     materials such as dictionaries, etc.; and vary by specificity,
     applicability, and availability;

  complexity consists of the nature, variety, and intricacy of tasks
     and the difficulty and originality involved in performing the
     work;

  scope and effect encompass the relationship between the breadth and
     depth of the work and the effect of work products and services
     within and outside the organization;

  personal contacts refer to contacts with persons not in the
     supervisory chain;

  purpose of contacts ranges from factual exchanges of information to
     situations involving significant or controversial issues and
     differing viewpoints, goals, or objectives;

  physical demands include physical characteristics such as agility,
     dexterity, and physical exertion--such as climbing, lifting,
     pushing, etc.; and

  work environment pertains to the risks and discomforts in the
     employee's physical surroundings or work assigned. 

As shown in table 1, each factor is broken down into graduated
levels.  Factors are composed of from three to nine levels with most
having four to six levels.  One factor--knowledge required by the
position--has the largest range of points, from 50 for level 1 to
1,850 for level 9. 



                                Table 1
                
                FES Factors and Points by Factor Levels


Factor                       1    2    3    4    5    6    7    8    9
-------------------------  ---  ---  ---  ---  ---  ---  ---  ---  ---
Knowledge required by the   50  200  350  550  750  950  1,2  1,5  1,8
 position                                                 50   50   50
Supervisory controls        25  125  275  450  650
Guidelines                  25  125  275  450  650
Complexity                  25   75  150  225  325  450
Scope and effect            25   75  150  225  325  450
Personal contacts           10   25   60  110
Purpose of contacts         20   50  120  220
Physical demands             5   20   50
Work environment             5   20   50
----------------------------------------------------------------------
\a The blank spaces in columns indicate that no further levels exist
for the corresponding factor. 

Source:  FES Primary Standard. 

To determine a position's GS grade, the agency typically compares
either the position description or information gathered through a
"desk audit" with the nine FES factors described in the
classification standard.\3 After all nine factors are evaluated, the
points for all factors are totaled, and the total for each position
is converted to a GS grade by using a conversion table (see table 2). 



                                Table 2
                
                     FES GS Grade Conversion Table

GS grade                                                   Point range
----------------------------------------  ----------------------------
GS-1                                                          190 -250
GS-2                                                          255 -450
GS-3                                                          455 -650
GS-4                                                          655 -850
GS-5                                                        855 -1,100
GS-6                                                      1,105 -1,350
GS-7                                                      1,355 -1,600
GS-8                                                      1,605 -1,850
GS-9                                                      1,855 -2,100
GS-10                                                     2,105 -2,350
GS-11                                                     2,355 -2,750
GS-12                                                     2,755 -3,150
GS-13                                                     3,155 -3,600
GS-14                                                     3,605 -4,050
GS-15                                                        4,055 -up
----------------------------------------------------------------------
Source:  FES Primary Standard. 


--------------------
\2 The point-factor system involves assigning a point value or weight
to each compensable factor and totaling the points assigned to obtain
a job worth score that measures the relative importance of each
position to an organization.  Narrative standards use fewer factors
to describe the important characteristics of the work, and the GS
grade is determined through nonquantitative analysis. 

\3 Desk audits typically consist of a trained classifier's
face-to-face interviews with the incumbent and supervisor and
observations of the work operations, sometimes including an
examination of work products. 


   APPROACH
------------------------------------------------------------ Letter :2

A contractor, with our supervision, developed a job content
questionnaire on the basis of the FES primary standard.  The
contractor distributed it to a stratified random sample of 2,060
pairs of incumbents and their supervisors and received responses from
1,639 incumbent/supervisor pairs, which represents an overall
response rate of about 80 percent.  Because individual federal
positions are classified through labor-intensive desk audits, it was
not practical for us to study the majority of FES occupations using
traditional classification methods. 

The contractor did, however, do desk audits of 78 judgmentally
selected positions and compared the audit results with the related
questionnaire responses.  These comparisons indicated a fairly high
correlation across occupations.  The validity coefficient between the
GS grades resulting from the desk audits and those from the
questionnaires was .80 when the incumbent and supervisor
questionnaire responses were averaged.\4 We considered this
correlation to be sufficiently high to validate the use of the job
content questionnaire results for comparing groups of occupations.\5
However, we cannot attest to the questionnaire's validity when used
across GS grades within occupations, for specific occupations, or for
individual positions.  Further, our study was not designed to
determine whether, and if so why, the job content reflected by the
questionnaires differed from that contained in the official job
descriptions, which are the bases for the actual GS grades. 

We used an OPM database to identify a representative segment of
incumbents and their supervisors in occupations with high, medium, or
low representations of women or minorities.  We defined occupations
with high, medium, and low female representation as those in which
women represented 70 percent or more, 31 to 69 percent, and 30
percent or less of incumbents, respectively.  We considered
occupations in which minorities represented more than 41 percent, 23
to 41 percent, or less than 23 percent of incumbents as those with
high, medium, and low minority representation, respectively. 
Examples of occupations with high female representation included
secretary, dental hygienist, medical clerk, dental assistant, and
occupational therapist.  Examples of occupations with high minority
representation included border patrol agent and computer and equal
employment opportunity specialists. 

We selected our sample of incumbents and their supervisors from a
total of 58 occupations, which collectively represented about 90
percent of the full-time permanent nonsupervisory employees covered
by FES when we designed our study.  Because preliminary analyses
indicated that more variation in undergrading and overgrading existed
among occupations with similar gender and minority representation
than between groups of occupations with different gender and minority
representations, we did our analyses on the 37 occupations for which
we had received completed questionnaires from at least 10 or more
incumbent/supervisor pairs, for a total of 1,358 pairs or positions. 
These 37 occupations represented almost one-quarter of the federal
white-collar workforce, or about 79 percent of the employees covered
by FES, and the results of our study are generalizable only to this
population.\6

On the basis of the average total factor level points derived from
the questionnaires completed by the incumbent and the supervisor, we
determined the GS grade for each position using the FES conversion
table (see table 2).  We compared the questionnaire grade with the
incumbent's actual GS grade and considered the position to be aptly,
or appropriately, graded if the questionnaire grade and the actual
grade were the same.  Otherwise, we considered positions to be
overgraded if the actual grade was higher than the questionnaire
grade and undergraded if the actual grade was lower than the
questionnaire grade. 

Our study was not designed to permit us to

  approximate the number of positions that appeared to be overgraded,
     undergraded, or aptly graded for the portion of the federal
     workforce to which the results of our study are generalizable;

  identify the causes of any overgrading or undergrading resulting
     from either (1) our use of the primary rather than the
     occupation-specific classification standards, (2) the agencies'
     application of classification standards to individual positions,
     or (3) management decisions regarding the work incumbents were
     actually assigned versus their job descriptions;

  determine whether any difference on the basis of gender or minority
     status was inherent in the design of FES, as a product either of
     the factors that constitute FES or the allocation of weight or
     the point range assigned to each factor; or

  calculate what pay adjustments, if any, should be made. 

Appendix I contains a more detailed discussion of the job content
questionnaire development and validation, sample selection, and
response rate calculation. 

To determine the effects of female or minority representation on
relative overgrading and undergrading, we used odds and odds ratios. 
We calculated the odds of occupations being undergraded rather than
aptly graded by dividing the number of positions undergraded by the
number aptly graded for groups of occupations.  To determine how much
more likely one group of occupations was to be undergraded than
another group, we divided the odds of being undergraded for one group
of occupations by the odds for the other group to form an odds ratio. 
We used the same procedures for overgrading. 

We used loglinear analysis to determine how the odds of occupations
being overgraded or undergraded versus aptly graded varied (1) across
the range of GS grades and (2) when the female or minority
representation of the occupation was high, medium, or low.  The
strength of this particular statistical approach is that multiple
variables can be analyzed simultaneously.  Appendix II provides more
detailed information on the calculation of odds and odds ratios and
loglinear models tested and the results obtained. 

To gain historical perspective, we reviewed previous studies of
federal classification issues.  We also conferred with federal
classification experts to obtain additional insights about possible
explanations for specific findings. 

This study should not be referred to as a "pay equity" study because
we examined only the relationship between job content and GS grades
assigned through the use of FES and whether that relationship varied
with the proportion of women or minorities in occupations. 

We obtained comments from OPM that are discussed on pages 11 through
12 and presented in appendix III.  We did our study from January 1990
to September 1995 in accordance with generally accepted government
auditing standards. 


--------------------
\4 A validity coefficient measures the consistency between two data
sets. 

\5 Psychological testing standards traditionally required validity
coefficients of at least .70 for all tests, and on that basis, we
conclude that our result is sufficiently valid.  However,
psychologists have acknowledged that coefficients as low as .30 can
be of practical value.  This is the only classification study we are
aware of in which desk audits were used to demonstrate that the
questionnaire results were similar to those which would be attained
in an actual position classification. 

\6 Because we could not obtain reliable estimates of the odds of
overgrading and undergrading for occupations with small numbers of
respondents, we deleted those 21 occupations with fewer than 10
incumbent/supervisor pairs. 


   RESULTS IN BRIEF
------------------------------------------------------------ Letter :3

For the nonsupervisory positions in the 37 occupations we studied,
our analyses suggest that the difference between the actual GS grades
and those we determined using a job content questionnaire was
directly related to the female and minority representation of the
occupations we examined.\7 If the actual grade was higher than the
questionnaire-derived grade, we considered the position to be
overgraded; if the actual grade was lower than the questionnaire
grade, we considered the position to be undergraded. 

The likelihood of a position being overgraded, rather than aptly
graded, increased as the incumbents' GS grades increased.  However,
the incumbents' grades had virtually no effect on the likelihood that
a position was undergraded versus aptly graded.  After statistically
eliminating this effect of the incumbents' GS grades, we found that
the occupations we studied with high female representation were more
likely to be undergraded rather than aptly graded compared with the
occupations having medium or low female representation.  As mentioned
above, we defined occupations with high female representation as
those in which 70 percent or more of the incumbents were women.  This
definition was used on the basis of the current literature when we
designed our study. 

The literature contained no consistent basis on which to define
minority representation.  On the basis of our past work, we initially
adopted a standard of more than 48 percent to define high minority
representation.\8 However, we found it necessary to adjust our
definition for high minority representation to occupations in which
more than 41 percent of the incumbents were minorities in order to
include at least two occupations with each possible mix of gender and
minority representation (e.g., low female, high minority
representation). 

We would have preferred that our original definition had provided a
sufficient mix of occupations in our sample.  And it is important to
note that about half of the incumbents in the total population of the
occupations defined by our study as having a high minority
representation were in fact nonminorities.  Within these parameters,
after eliminating the effects of the incumbents' GS grades, we found
that occupations with high minority representation were more likely
to be overgraded rather than aptly graded in comparison with the
occupations having medium or low minority representation. 

The National Performance Review has contended that the current
federal classification systems have too many occupations and grades
and has recommended that a more flexible "broad-banded" system be
adopted.  OPM is currently, within the existing statutory framework,
planning to revise the classification standards and increase
classification oversight.  Our study suggests any new system should
be closely monitored to ensure that unintended disparities are
identified and addressed. 


--------------------
\7 We developed our job content questionnaire on the basis of the FES
primary standard that serves as the framework for individual
classification standards written for each occupation.  The actual GS
grades were assigned using these occupation-specific standards. 
Further, the questionnaire was designed and validated to achieve our
review objectives relative to comparing groups of occupations.  It
was not designed as and is not a valid substitute for traditional
classification methods.  Therefore, the questionnaire should not be
used to draw definitive conclusions regarding overgrading or
undergrading of individual positions. 

\8 When we designed our study, minorities comprised approximately 32
percent of the workforce covered by FES.  We initially defined
occupations with high minority representation as those in which more
than 48 percent (150 percent of the 32 percent minority workforce
representation) of the incumbents were minorities. 


   EFFECTS OF FEMALE AND MINORITY
   REPRESENTATION ON RELATIVE
   OVERGRADING AND UNDERGRADING
------------------------------------------------------------ Letter :4

To evaluate whether gender or minority representation had an effect
on the variation between the actual grades and the questionnaire
grades, we statistically eliminated the effect of the incumbents' GS
grades.\9 Analysis of the remaining variation showed that occupations
with high female representation were 1.77 times more likely to be
undergraded rather than aptly graded compared with occupations having
a low or medium female representation.  Occupations with high
minority representation were 2.18 times more likely to be overgraded
rather than aptly graded compared with occupations having a low or
medium minority representation.\10

Classification experts with whom we consulted about our results and
the available literature offered a few occupation-specific hypotheses
about possible causes.  For example, key occupations with high
minority representation that appeared to be overgraded included (1)
border patrol agents, (2) equal employment opportunity and compliance
specialists, and (3) computer specialists.  Previous studies of
federal classification issues maintained that FES was ineffective for
specialists such as law enforcement related occupations because
physical demands and work environment are not highly valued FES
factors but are considered significant in these occupations. 

Although empirical data are lacking, the classification experts we
consulted suggested that when equal employment opportunity
occupations were established in the 1970s, they involved a heavy
workload of cases and, even though not recognized by FES, the GS
grades of these occupations may have been increased on that basis. 
Furthermore, private sector wages may have resulted in overgrading
positions in computer-related occupations.  Explanations are somewhat
less evident regarding occupations with high female representation,
which appear more likely to be undergraded. 


--------------------
\9 The likelihood or odds of a position being overgraded increased as
the GS grade increased; that is, as the grade increased by one GS
grade, the odds that a position was overgraded versus aptly graded
increased by a factor of 1.64.  For example, the odds of positions
being overgraded in occupations with an average grade of GS-9 were
approximately 5 to 1 (i.e., five positions were overgraded for every
one that was aptly graded), while the odds of positions being
overgraded in occupations with an average grade of GS-10 were about
8.2 to 1.  The factor of 1.64 (8.2 / 5 = 1.64) indicates that
positions in the higher graded occupations were 1.64 times more
likely than those in the lower graded occupations to be overgraded. 
At the 95 percent level of confidence, as the grade increased by one
GS grade, the odds that a position was overgraded versus aptly graded
increased by a factor ranging from 1.53 to 1.77.

The GS grade had no significant effect on the odds that a position
was undergraded versus aptly graded. 

\10 At the 95 percent level of confidence, occupations with high
female representation were from 1.33 to 2.35 times more likely to be
undergraded than occupations with medium or low female
representation, and occupations with high minority representation
were from 1.62 to 2.94 times more likely to be overgraded than those
with medium or low representation. 


   CURRENT EFFORTS TO REVAMP
   CLASSIFICATION STANDARDS AND
   SYSTEMS
------------------------------------------------------------ Letter :5

Critics of the federal classification system, including reports from
the National Academy of Public Administration and the National
Performance Review, have argued that the classification system is
overly complex, with too many occupations and GS grades, and that a
less rigid system would be more effective.  They have recommended
fewer occupations and more flexible broad-banded grade structures. 

OPM officials told us recently that, within the existing statutory
framework, OPM plans to revise the classification standards and
increase its oversight of various processes including classification. 
A current proposal for rewriting classification standards would
reduce the inventory of 442 white-collar classification standards to
about 74.  Rather than individual occupations, the new standards
would focus on the 22 "job families" of related occupations with
separate standards, as applicable, for professional, administrative,
technical, and clerical positions.\11

OPM has also established a new oversight office, which, among other
things, is planning various governmentwide policy studies.  OPM has
tentatively allocated about 145 staff years to this effort; most of
these resources are located in field offices rather than at
headquarters.  One of the highest priorities will be a governmentwide
classification study, with particular emphasis on determining the
accuracy of "border grades"--those grades most likely to be placed at
the lower and upper limits of any newly created grade bands.  A team
is examining options for doing this study, and work on the study is
scheduled to begin early in fiscal year 1996. 


--------------------
\11 "Job families" consist of related occupations that are grouped
together such as the General Administrative, Clerical, and Office
Service Group; the Accounting and Budget Group; the Physical Science
Group; etc. 


   CONCLUSIONS
------------------------------------------------------------ Letter :6

Although FES is considered a more orderly or rigorous method than
other federal classification systems, our study identified
differences in the grading of positions in occupations with high
representations of women or minorities.  The National Performance
Review and other studies suggest that the current classification
systems should be abandoned in favor of more flexible, broad-banded
systems.  The results of our study indicate that it is important that
policymakers closely monitor any new systems to ensure that (1)
unintended disparities are identified so that they can be corrected
and (2) the national policy underlying the current classification
system--that jobs be classified so that pay is equal for
substantially equal work--is being satisfactorily achieved.  Since
OPM is in the process of substantially revising the classification
and oversight systems, we are making no recommendations in this
report. 


   AGENCY COMMENTS AND OUR
   EVALUATION
------------------------------------------------------------ Letter :7

OPM provided written comments on a draft of this report.  (See app. 
III.) OPM took issue with our methodology, saying that it was
insufficient to support our findings.  OPM also discussed its plans
to further explore job classification accuracy issues. 

OPM took exception with our methodology in two respects.  First, it
believes we inappropriately used the primary classification standard
rather than occupation-specific standards as the basis for our job
content questionnaire.  OPM said that the primary standard was
designed to be used as an overall outline wherein more specific
standards would be developed, not as a basis for evaluating
individual positions.  Although we used the primary standard rather
than the occupation-specific standards in the development of our
methodology, we examined the specific standard for several
occupations in our sample to see if we could identify any ways in
which the use of the occupation-specific standard might have led to a
different result.  We did not identify any such effect.  We also
asked OPM's classification experts to identify occupations in our
sample for which the specific standards were, in their view,
sufficiently different from the primary standard that our results
would have been affected in identifiable ways.  They did not identify
any such occupations.  Thus we continue to believe that our use of
the primary standard was appropriate and that our methodology
produced useful results. 

OPM's second exception with our methodology was our use of a job
content questionnaire rather than traditional desk audits to assign
grades to positions.  OPM said that our use of a questionnaire
resulted in employees and supervisors, unfamiliar with FES ground
rules, being asked to select generic phrases that were not in context
and that this in turn resulted in the grades we assigned being less
credible than those derived by federal agencies.  We acknowledge in
our text that actual GS grades are assigned on the basis of
occupation-specific standards and that the desk audit is a typical
way to assign a grade to a position.  As noted in the text, desk
audits are labor-intensive, and it was not practical for us to study
the majority of FES occupations using traditional classification
methods.  Because of this, we took care to validate our results. 
First, we had a contractor do desk audits on positions in a number of
occupations in our sample.  Next, we compared the results of those
desk audits with the questionnaire results for those positions.  This
comparison showed a fairly high correlation between the GS grades
resulting from desk audits and those from the questionnaire.  Thus,
we believe that our methodology is appropriate to identify patterns
of overgrading and undergrading among groups of occupations with
different representations of women or minorities. 

OPM also questioned our study results by comparing them with other
studies.  More specifically, OPM said that other agencies' studies
and OPM's classification appeals data indicated lower levels of
misclassification than our study.  We are unaware of any recent
studies or appeals data in which a direct comparison with our study
could be meaningful.  Although OPM's most recent report on the
overall federal white-collar position classification accuracy
indicated a lower level of misclassification than our study, it was
published in 1983.  We acknowledge that classification appeals also
indicate a lower level of misclassification than our study.  However,
classification experts with whom we consulted said that appeals data
are unlikely to represent those federal employees whose positions may
be overgraded.  As indicated by the Merit System Protection Board
(MSPB), almost no one files a classification appeal.\12

Finally, OPM said that it shares with us the need to ensure that the
federal government's classification systems and their applications
are fair and unbiased.  OPM said that to this end, its newly designed
oversight program will have a major focus on ensuring that current
and new classifications systems advance the merit principles of equal
pay and the efficient and effective use of the federal workforce. 
OPM said that it expects to decide on the classification review
design by the end of fiscal year 1995 and begin work on the review in
early fiscal year 1996. 


--------------------
\12 According to MSPB only 240 of the government's 2.1 million
civilian nonpostal employees filed an appeal in 1988, or about one
one-hundredth of 1 percent. 


---------------------------------------------------------- Letter :7.1

We are sending copies of this report to interested Members of
Congress and congressional committees that have responsibilities for
public sector employment issues, the Director of the Office of
Personnel Management, and other interested parties.  Copies will also
be made available to others upon request. 

Major contributors to this report are listed in appendix IV.  If you
have any questions about the report, please call me at (202)
512-7824. 

Nancy Kingsbury
Director
Planning and Reporting


QUESTIONNAIRE DEVELOPMENT, SAMPLE
SELECTION, RESPONSE RATE
CALCULATION, AND VALIDATION
METHODOLOGY
=========================================================== Appendix I

Using the competitive bid process, we contracted with a national
management consultant--Barrett & Associates, Inc., of Akron, Ohio--to
(1) develop a job content questionnaire that enabled the contractor
to estimate GS grades for positions in our nationwide sample using
input from the incumbents and their supervisors, (2) distribute the
questionnaire to a sample of incumbent/supervisor pairs attaining at
least an 80 percent response rate, (3) develop a semistructured
interview guide for completing desk audits, (4) validate the
questionnaire through the use of desk audits, and (5) analyze the
questionnaire responses.\1 The analyses were done to determine
whether a link existed between the GS grades assigned to positions
through the use of the Factor Evaluation System (FES) and the number
of women or minorities in occupations that we included in our study. 

We selected the sample of incumbent/supervisor pairs and worked
closely with the contractor providing supervision throughout the
process.  Because the preliminary analyses showed that more variation
existed within groups of occupations rather than between those
groups, we refined the analyses of the questionnaire responses as
described in appendix II. 

In addition to working with the contractor, we consulted periodically
with an ad hoc panel of experts that provided technical guidance
during the early design phase of our study.  Our panel consisted of

  Ms.  Ruth Rogers, former Chief, Standards Division, Department of
     Personnel, Government of the District of Columbia, who provided
     staff assistance to the District's pay equity study;\2

  Dr.  Donald Schwab, Professor of Business Research and Industrial
     Relations, University of Wisconsin-Madison, who has written
     extensively on the issue of comparable worth; and

  Dr.  Ronnie Steinberg, Professor of Sociology and Women's Studies,
     Temple University, who has considerable experience with pay
     equity issues and job content questionnaires. 

We also consulted with Dr.  David Rindskopf, Professor, Graduate
School and University Center, City University of New York, for
assistance with our sample selection methodology. 

After we completed our analyses, we shared our results with and
obtained informal comments from five federal officials with
classification experience.  In addition to a representative from OPM
and GAO's personnel office, we selected three of these experts from a
list of recommended candidates provided at our request by the
Classification and Compensation Society, a professional organization
of federal classifiers and other personnel specialists.  The
classification experts included a mix of male, female, minority, and
nonminority individuals who worked in OPM's then Personnel Systems
and Oversight Group and in the personnel offices of the Federal
Aviation Administration, the Department of Defense, the Library of
Congress, and the General Accounting Office. 


--------------------
\1 Desk audits consist of face-to-face interviews between trained
classifiers and the incumbent and supervisor to identify and observe
work operations and products.  The validation was done to determine
whether our questionnaire could be used to estimate GS grades similar
to those that would be attained in actual desk audits.  When we
designed our study, we set a goal of achieving a .80 validity
coefficient, which measures the consistency between two data sets. 

\2 According to a District of Columbia official, in July 1990, the
District contracted with a consulting firm to do a pay equity study,
and in April 1994, the contractor provided a final report with
recommendations. 


   QUESTIONNAIRE DEVELOPMENT AND
   GS GRADE ESTIMATION
--------------------------------------------------------- Appendix I:1

We developed a job content questionnaire that enabled us to estimate
GS grades for positions covered by FES, a point factor position
classification system the federal government used to classify 77 of
the 455 white-collar occupations when we designed our study.\3 On the
basis of the factor descriptions in the FES primary standard, we
constructed questions that allowed us to determine the appropriate
level for each factor.\4 Table I.1 shows the points associated with
each factor level. 



                               Table I.1
                
                FES Factors and Points by Factor Levels


Factor                       1    2    3    4    5    6    7    8    9
-------------------------  ---  ---  ---  ---  ---  ---  ---  ---  ---
Knowledge required by the   50  200  350  550  750  950  1,2  1,5  1,8
 position                                                 50   50   50
Supervisory controls        25  125  275  450  650
Guidelines                  25  125  275  450  650
Complexity                  25   75  150  225  325  450
Scope and effect            25   75  150  225  325  450
Personal contacts           10   25   60  110
Purpose of contacts         20   50  120  220
Physical demands             5   20   50
Work environment             5   20   50
----------------------------------------------------------------------
\a The blank spaces in columns indicate that no further levels exist
for the corresponding factor. 

Source:  FES Primary Standard. 

Figures I.1 and I.2 show an excerpt from the FES primary standard and
the resulting question that we included in our job content
questionnaire, respectively. 

   Figure I.1:  Excerpt from the
   FES Primary Standard

   (See figure in printed
   edition.)

   Figure I.2:  Excerpt from the
   Job Content Questionnaire

   (See figure in printed
   edition.)

The GS grade is determined by totaling the points assigned to each of
the nine factors and using the grade conversion table shown in table
I.2. 



                               Table I.2
                
                  Conversion of FES Points to GS Grade

GS grade                                                   Point range
----------------------------------------  ----------------------------
GS-1                                                          190 -250
GS-2                                                          255 -450
GS-3                                                          455 -650
GS-4                                                          655 -850
GS-5                                                        855 -1,100
GS-6                                                      1,105 -1,350
GS-7                                                      1,355 -1,600
GS-8                                                      1,605 -1,850
GS-9                                                      1,855 -2,100
GS-10                                                     2,105 -2,350
GS-11                                                     2,355 -2,750
GS-12                                                     2,755 -3,150
GS-13                                                     3,155 -3,600
GS-14                                                     3,605 -4,050
GS-15                                                        4,055 -up
----------------------------------------------------------------------
Source:  FES Primary Standard. 

To determine whether incumbents could readily understand the
questionnaire and complete it within a reasonable time period, we
completed three sets of pretests.  In total, we selected about 30
incumbents and supervisors who were located in the Cleveland
metropolitan area and who represented a range of GS grades and
occupations covered by FES.  After observing them as they completed
the questionnaire, we interviewed each incumbent or supervisor to
identify how the questionnaire could be improved; we rewrote or
edited most of the questions on the basis of the information they
provided.  During the initial pretest, we also revised our
semistructured interview guide for use in completing subsequent desk
audits. 

On the basis of questionnaire responses received from incumbents and
their supervisors, we estimated the appropriate GS grade for each
position in our sample by (1) determining the appropriate level (and
corresponding points) for each of the nine factors, (2) averaging the
total points computed separately for the incumbent and the
supervisor, and (3) using the FES points-to-grade conversion table to
assign a GS grade to the position.  We decided to average the input
from the incumbent and the supervisor to balance the views of those
who would place more reliance on the input of incumbents versus that
of supervisors.  Table I.3 shows an example of how we estimated the
GS grade for one position in our sample. 



                               Table I.3
                
                Example of GS Grade Estimation Based on
                 Incumbent and Supervisor Questionnaire
                               Responses


                                                                Averag
                                                                     e
                                Factor          Factor           total
Factor                           level  Points   level  Points  points
------------------------------  ------  ------  ------  ------  ------
Knowledge required by                4     550       3     350
 the position
Supervisory controls                 2     125       2     125
Guidelines                           2     125       1      25
Complexity                           3     150       1      25
Scope and effect                     2      75       4     225
Personal contacts                    3      60       1      10
Purpose of contacts                  1      20       1      20
Physical demands                     2      20       1       5
Work environment                     1       5       2      20
======================================================================
Total points                             1,130             805     967
Estimated GS grade                                                GS-5
----------------------------------------------------------------------
Note:  The blank spaces in columns indicate that we estimated GS
grades by averaging the total points on the basis of input from the
incumbent and the supervisor rather than the points assigned to each
factor. 


--------------------
\3 A point factor position classification system uses a set of
factors and factor weights to order positions hierarchically in terms
of their value to an employer.  FES uses the following nine factors
to describe the duties and responsibilities of a position:  knowledge
required by the position, supervisory controls, guidelines,
complexity, scope and effect, personal contacts, purpose of contacts,
physical demands, and work environment.  Each factor is broken down
into graduated levels.  Factors are composed of from three to nine
levels. 

\4 The FES primary standard serves as the framework for individual
classification standards written for each occupation.  We compared
the occupation-specific standards with the primary standard for four
occupational series--computer operations, border patrol agent, equal
employment opportunity, and equal opportunity compliance--and
determined that these occupation-specific standards appeared to be
within the framework of the primary standard. 


   SAMPLE SELECTION
--------------------------------------------------------- Appendix I:2

We selected our nationwide sample from the full-time permanent
nonsupervisory incumbents in the 77 occupations for which an FES
standard had been in existence for at least 1 year when we completed
our study design in May 1992.  Because of limited resources, we
excluded incumbents who (1) were stationed outside of the continental
United States or (2) worked for agencies with less than 500
employees.  Each of the 77 occupations included from 35 to 91,769
incumbents for a total of 441,189 full-time permanent nonsupervisory
incumbents.  Women constituted about 61 percent of the total
workforce covered by FES and minorities, approximately 32 percent. 
We used OPM's Central Personnel Data File (CPDF), updated as of June
1992, to select our sample.  These were the most recent data
available when we designed our study.  We did not independently
verify the accuracy of this database. 

We defined each of the 77 occupations covered by FES as having a
high, medium, or low representation of women or minorities.  On the
basis of the current literature, we defined occupations with high,
medium, and low female representation as those in which women
represented 70 percent or more, 31 to 69 percent, and 30 percent or
less of the incumbents, respectively.  The literature contained no
consistent basis on which to define minority representation;
therefore, on the basis of our past work, we initially adopted a
standard of more than 48 percent (150 percent of the 32 percent
minority workforce representation) to define high minority
representation; less than 16 percent (50 percent of 32 percent), low
minority representation; and 16 to 48 percent, medium minority
representation.  However, in order to include in our sample at least
two occupations with each possible mix of gender and minority
representation (e.g., low female, high minority representation), we
found it necessary to adjust our definitions for occupations with
high, medium, and low minority representation to those in which
minorities represented more than 41 percent, 23 to 41 percent, and
less than 23 percent of incumbents, respectively.  Table I.4 shows
the distribution of the 77 occupations in a nine-cell matrix
configured according to female and minority representation. 



                               Table I.4
                
                 Distribution of the 77 FES Occupations


Female representation               High    Medium       Low     Total
------------------------------  --------  --------  --------  ========
High                                   6        14         2        22
Medium                                12        10         5        27
Low                                    3         3        22        28
======================================================================
Total                                 21        27        29        77
----------------------------------------------------------------------
Source:  GAO analysis of data obtained from OPM. 

From the 77 occupations covered by FES, we selected 58 on the basis
of four characteristics--number of incumbents, PATCO (professional,
administrative, technical, clerical, and other) category,\5 job
family,\6 and GS grade distribution.  First, we chose occupations in
each matrix cell with the largest number of incumbents.  Second, we
examined the PATCO category of the occupations selected within each
cell and chose additional occupations to include all categories. 
Third, we reviewed the job families represented by the occupations
already selected and chose additional occupations increasing the
number of families included in our study to 17 out of a total of 22. 
Finally, we examined the GS grade distributions of the occupations
selected and chose occupations that included grades not previously
selected within each row and column of the matrix.  Table I.5 shows
the female and minority representation, PATCO category, and number of
full-time permanent nonsupervisory incumbents for each of the 77
occupations covered by FES when we selected our sample as well as the
58 occupations selected for inclusion in our sample. 



                                    Table I.5
                     
                       Female and Minority Representation,
                     PATCO Category, and Number of Incumbents
                      for the 77 Occupations Covered by FES


                                                                       Full-time
                                                                       permanent
Occupational                                                      nonsupervisory
series\a                      Female      Minority    PATCO\b         incumbents
------------  --------------  ----------  ----------  ----------  --------------
318           Secretary       High        Medium      C                   91,769

334           Computer        Medium      Medium      A                   43,958
              specialist

1102          Contracting     Medium      Medium      P                   25,355

525           Accounting      High        Medium      C,T\c               18,081
              technician

621           Nursing         Medium      High        T                   14,984
              assistant

305           Mail and file   Medium      High        C                   14,630

592           Tax examining   High        Medium      C,T\d               13,271

1910          Quality         Low         Low         A                   12,163
              assurance

203           Personnel       High        High        C,T\d               11,640
              clerical and
              assistance

511           Auditing        Medium      Low         P                   11,413

560           Budget          High        Medium      A                   11,099
              analysis

830           Mechanical      Low         Low         P                   10,726
              engineering

679           Medical clerk   High        High        C                   10,697

510           Accounting      Medium      Medium      P                    8,838

335           Computer clerk  High        Medium      C,T\e                8,353
              and assistant

332           Computer        Medium      High        T                    6,833
              operation

610           Nurse           High        Medium      P                    5,746

1320          Chemistry       Low         Low         P                    5,347

83            Police          Low         Medium      O                    5,096

80            Security        Medium      Medium      A                    4,616
              administration

391           Telecommunicat  Low         Low         A                    4,568
              ions

644           Medical         Medium      Medium      P                    4,491
              technologist

457           Soil            Low         Low         P                    4,027
              conservation

540           Voucher         High        Medium      C                    3,978
              examining

(561)         (Budget         (High)      (Medium)    (C,T\d)            (3,937)
              clerical and
              assistance)

85            Security guard  Low         High        O                    3,882

(1370)        (Cartography)   (Low)       (Low)       (P)                (3,817)

460           Forestry        Low         Low         P                    3,764

(544)         (Civilian pay)  (High)      (Medium)    (C,T\e)            (3,524)

(819)         (Environmental  (Low)       (Low)       (P)                (3,461)
              engineering)

950           Paralegal       High        Medium      A                    3,460
              specialist

18            Safety and      Low         Low         A                    3,420
              occupational
              health
              management

1035          Public affairs  Medium      Low         A                    3,202

1896          Border patrol   Low         High        O                    3,176
              agent

475           Agricultural    Low         Low         P                    3,088
              management

1311          Physical        Low         Low         T                    2,987
              science
              technician

(545)         (Military pay)  (High)      (Medium)    (C,T\e)            (2,935)

(840)         (Nuclear        (Low)       (Low)       (P)                (2,873)
              engineering)

681           Dental          High        High        T                    2,660
              assistant

620           Practical       High        High        T                    2,563
              nurse

647           Diagnostic      Medium      Medium      T                    2,433
              radiologic
              technologist

2134          Shipment        High        Medium      C                    2,070
              clerical and
              assistance

622           Medical supply  Medium      High        T                    1,986
              aide and
              technician

260           Equal           Medium      High        A                    1,907
              employment
              opportunity

(486)         (Wildlife       (Low)       (Low)       (P)                (1,850)
              biology)

1173          Housing         Medium      Medium      A                    1,841
              management

(458)         (Soil           (Medium)    (Low)       (T)                (1,835)
              conservation
              technician)

649           Medical         Medium      High        T                    1,819
              instrument
              technician

350           Equipment       Medium      High        C                    1,779
              operator

808           Architecture    Low         Medium      P                    1,686

360           Equal           Medium      High        A                    1,526
              opportunity
              compliance

(1980)        (Agricultural   (Low)       (Low)       (T)                (1,438)
              commodity
              grading)

1371          Cartographic    Medium      Low         T                    1,358
              technician

(482)         (Fishery        (Low)       (Low)       (P)                (1,358)
              biology)

690           Industrial      Medium      Low         P                    1,247
              hygiene

1822          Mine safety     Low         Low         T                    1,190
              and health

1889          Import          Medium      Medium      A                    1,159
              specialist

630           Dietician and   High        Medium      P                    1,111
              nutritionist

436           Plant           Low         Medium      P                    1,097
              protection and
              quarantine

701           Veterinary      Low         Low         P                      834
              medical
              science

188           Recreation      Medium      Medium      A                      805
              specialist

1040          Language        Medium      High        A                      585
              specialist

(651)         (Respiratory    (Medium)    (High)      (T)                  (496)
              therapist)

361           Equal           High        High        T                      486
              opportunity
              assistance

270           Federal         Medium      Medium      A                      416
              retirement
              benefits

1720          Education       Medium      High        P                      369
              program

(485)         (Wildlife       (Low)       (Low)       (P)                  (365)
              refuge
              management)

682           Dental hygiene  High        Low         T                      335

(2121)        (Railroad       (Low)       (Low)       (A)                  (322)
              safety)

309           Correspondence  High        High        C                      310
              clerk

(2123)        (Motor carrier  (Low)       (Low)       (A)                  (284)
              safety)

(669)         (Medical        (High)      (Medium)    (A)                  (170)
              records
              administration
              )

(1161)        (Crop           (Low)       (Low)       (A)                  (109)
              insurance
              administration
              )

(1162)        (Crop           (Low)       (Low)       (A)                   (54)
              insurance
              underwriting)

631           Occupational    High        Low         P                       49
              therapist

(1884)        (Customs        (Low)       (High)      (O)                   (47)
              patrol
              officer)

(160)         (Civil rights   (Medium)    (High)      (A)                   (35)
              analysis)

================================================================================
Subtotal/                                                                412,279
included in
study

Subtotal/                                                               (28,910)
not included
in study

================================================================================
Total                                                                    441,189
--------------------------------------------------------------------------------
Note:  This table includes occupational series, or occupations,
covered by FES that had been in existence for at least 1 year as of
May 1992. 

\a We selected incumbents for our sample from the 58 occupational
series not shown in parentheses. 

\b The PATCO category indicates the general characteristics of the
work done within each federal white-collar occupation and is
represented as Professional, Administrative, Technical, Clerical, or
Other. 

\c The PATCO category for this occupation is Clerical for GS grades 1
to 3 and Technical for grades 4 and above. 

\d The PATCO category for this occupation is Clerical for GS grades 1
to 5 and Technical for grades 6 and above. 

\e The PATCO category for this occupation is Clerical for GS grades 1
to 4 and Technical for grades 5 and above. 

Source:  GAO analysis of data obtained from OPM. 

We selected no more than 11 occupations for each matrix cell because
we planned to validate the job content questionnaire by completing
two sets of 100 desk audits that would each (1) include at least one
position from each occupation in our sample and (2) be evenly
distributed among the 9 matrix cells.  Table I.6 shows the
distribution of the 58 occupations selected for inclusion in our
sample by matrix cell. 



                               Table I.6
                
                   Distribution of the 58 Occupations
                         Included in the Sample


Female representation               High    Medium       Low     Total
------------------------------  --------  --------  --------  ========
High                                   6        10         2        18
Medium                                10        10         4        24
Low                                    2         3        11        16
======================================================================
Total                                 18        23        17        58
----------------------------------------------------------------------
Source:  GAO analysis of data obtained from OPM. 

After selecting the 58 occupations, we completed a pilot test by
distributing the job content questionnaire to 389 pairs of incumbents
and their supervisors who were located in either the Cleveland, OH,
or Washington, D.C.  areas and who represented a range of GS grades
and occupations included in our sample.  Because the CPDF does not
identify a specific address or supervisor for incumbents, we
forwarded the questionnaires to the appropriate agency personnel
offices for distribution.  Pairs of trained job analysts composed of
at least one female and one minority completed the first set of desk
audits for 100 of the 257 positions for which the incumbent and the
supervisor returned a questionnaire.\7 Of the 100 positions, we
included in our analyses the 84 positions for which the incumbent and
the supervisor provided complete responses to all questionnaire
items.  To ensure the independence of the validation process, the
contractor instructed the job analysts not to review the
incumbent/supervisor responses to the questionnaire for any position
before they completed a desk audit. 

On the basis of the pilot test, we determined that (1) incumbents at
higher GS grades tended to undervalue their positions when compared
to the desk audit, while incumbents at lower grades tended to
overvalue their positions and (2) the grades of incumbents included
in our study were not evenly distributed across the matrix rows and
columns.  As a result, the validity coefficient between GS grades
estimated on the basis of the desk audits versus incumbent/supervisor
questionnaire responses was .74.  Because the combination of the two
effects threatened to distort the results of our planned statistical
comparisons, we stratified our sample by classifying the incumbents
of the 58 occupations into one of seven groups, or strata, on the
basis of GS grade:  grades 1 to 4, grade 5, grade 6, grades 7 to 8,
grades 9 to 10, grade 11, and grades 12 to 15.  We then determined
the number of incumbent/supervisor pairs needed within each matrix
cell using a complex balancing design to ensure that the row and
column totals would be about equal.  This stratified sampling
strategy enabled us to balance the grade distribution of incumbents
selected within each row and column of the matrix, and thus,
eliminate any grade level effect in subsequent analyses. 

We randomly selected our sample of full-time permanent nonsupervisory
incumbents from the 58 occupations that met the criteria for each
matrix cell and GS grade stratum and distributed the job content
questionnaire to 2,233 incumbents and their supervisors.  Because of
the random selection process, we did not select incumbents from 3 of
the 58 occupational series--import specialist, education program, and
correspondence clerk.  Table I.7 shows the distribution of the 2,233
incumbents in a matrix configured according to female and minority
representation and strata. 



                               Table I.7
                
                Distribution of the 2,233 Incumbents by
                 Female and Minority Representation and
                                 Strata


Female
representati
on            GS grade strata             High  Medium     Low   Total
------------  ------------------------  ------  ------  ------  ======
High          GS-1 to 4                     45      44       1      90
              GS-5                          65      66      19     150
              GS-6                          30      30      30      90
              GS-7 to 8                     30      30      29      89
              GS-9 to 10                    30      30      12      72
              GS-11                          3      44      15      62
              GS-12 to 15                    1     144       1     146
======================================================================
              Subtotal                     204     388     107     699
Medium        GS-1 to 4                     30      16      44      90
              GS-5                          50      50      50     150
              GS-6                          30      30      30      90
              GS-7 to 8                     30      30      30      90
              GS-9 to 10                    30      30      30      90
              GS-11                         42      28      20      90
              GS-12 to 15                  115      19      50     184
======================================================================
              Subtotal                     327     203     254     784
Low           GS-1 to 4                     15      30      45      90
              GS-5                          35      34      81     150
              GS-6                          30      30      30      90
              GS-7 to 8                     30      30      30      90
              GS-9 to 10                    30      30      30      90
              GS-11                         45      18      27      90
              GS-12 to 15                   34      19      97     150
======================================================================
              Subtotal                     219     191     340     750
======================================================================
Total                                      750     782     701   2,233
----------------------------------------------------------------------
Source:  GAO analysis of data obtained from OPM. 

In addition to the sample of 2,233 incumbent and supervisor pairs, we
also selected a supplemental sample of 303 pairs to enable us to
complete a second set of desk audits expeditiously.  We selected the
supplemental sample from those incumbents in the 58 occupations who
were located in one of three geographical areas--Washington, D.C.,
Dayton/Cincinnati, OH, or Los Angeles, CA--to represent incumbents
working in the eastern, central, and western United States.  Because
we did not randomly select the pairs in the supplemental sample from
all incumbents working in the 58 occupations covered by FES, we did
not include their questionnaire responses in our response rate
calculation or analyses. 


--------------------
\5 OPM assigns a PATCO category to each white-collar occupation on
the basis of the general subject matter of work, level of difficulty
or responsibility, and educational requirements.

Professional occupations require incumbents to use discretion and
judgment to apply knowledge acquired through education or training
equivalent to a bachelor's degree in a specialized field.

Administrative occupations involve the exercise of analytical ability
and personal responsibility to apply concepts and
practices--typically learned through a general college education or
progressively responsible work--to one or more fields of management.

Technical occupations consist of nonroutine work that is learned
on-the-job or from specialized training less than that represented by
college graduation to support professional or administrative fields.

Clerical occupations require incumbents to do structured work
according to established policies, which are learned through training
or work experience, to support office operations.

Other occupations include those miscellaneous occupations that are
not included in one of the four other categories. 

\6 Job families consist of related occupations that are numbered
using the same multiple of 100.  For example, GS-300, the general
administration, clerical, and office services group includes the mail
and file (GS-305), computer operation (GS-332), and
telecommunications (GS-391) occupations. 

\7 Although the majority of the job analysts had extensive desk audit
experience, the contractor provided the analysts with comprehensive
training that included writing job descriptions and classifying jobs
through the use of FES. 


   RESPONSE RATE CALCULATION
--------------------------------------------------------- Appendix I:3

We forwarded the job content questionnaires to the appropriate agency
personnel offices for distribution to each of the 2,233
incumbent/supervisor pairs.  For 179 pairs, agency officials notified
us that either the incumbent or the supervisor no longer held the
position indicated by the CPDF or were located outside of the United
States.  As planned, we eliminated these pairs from our study.  Of
the remaining 2,054 pairs, we received questionnaires from 1,633
pairs of respondents, for a response rate of 80 percent.  Table I.8
shows the disposition of each of the 2,233 incumbent/supervisor pairs
in our sample. 



                               Table I.8
                
                  Disposition of Incumbent/Supervisor
                          Pairs in the Sample

----------------------------------------------------------  ----------
Incumbent/supervisor pairs eliminated from the study
----------------------------------------------------------------------
Incumbent resigned or terminated                                    63
Incumbent transferred to another agency                             48
Incumbent in different occupation than one                          29
 identified by the CPDF
Incumbent or supervisor retired                                     26
Incumbent or supervisor outside the United States                    3
Incumbent in position not covered by FES                             9
Incumbent deceased                                                   1
======================================================================
Subtotal                                                         179\a

Incumbent/supervisor pairs in the study
----------------------------------------------------------------------
Respondents                                                      1,633
Nonrespondents                                                   421\b
======================================================================
Subtotal                                                         2,054
======================================================================
Total incumbent/supervisor pairs in sample                       2,233
----------------------------------------------------------------------
\a Of the 179 incumbent/supervisor pairs, we eliminated 177 pairs
from the study on the basis of factors relating to the incumbent. 
Two were eliminated on the basis of factors relating to the
supervisor. 

\b The 421 pairs of nonrespondents consisted of (1) 349 pairs for
which either the incumbent, the supervisor, or both did not respond
to our questionnaire after three follow-up efforts and (2) 72 pairs
for which we were unable to forward a questionnaire to either the
incumbent, the supervisor, or both for reasons which did not
eliminate the pairs from our study (e.g., either the incumbent or the
supervisor was on extended leave). 


   OCCUPATIONS INCLUDED IN THE
   STUDY ANALYSES
--------------------------------------------------------- Appendix I:4

For 201 of the 1,633 pairs of respondents, either the incumbent, the
supervisor, or both left some questionnaire items unanswered. 
Therefore, we included the remaining 1,432 pairs in our preliminary
analyses.  On the basis of the incumbent/supervisor questionnaire
responses, we estimated the GS grade for each of the 1,432 positions
and compared this grade with the position's actual grade.  We
considered positions to be appropriately graded when the actual grade
equalled the questionnaire grade; otherwise, we considered the
position to be overgraded if the actual grade was higher than the
questionnaire grade; and undergraded if the actual grade was lower
than the questionnaire grade. 

When we designed this study, we planned to compare the overgrading
and undergrading among groups of occupations with different gender
and minority representations or among matrix rows and columns. 
However, preliminary analyses showed that more variation in
overgrading and undergrading existed within the same row or column
rather than between different rows or columns.  For this reason, we
analyzed the 37 occupations for which we had received completed
questionnaires from at least 10 or more incumbent/supervisor pairs. 
We did not include the remaining 18 occupations in our analyses
because we could not obtain reliable estimates of overgrading and
undergrading for an occupation with less than 10 pairs of
respondents.\8 The 37 occupations included 1,358 incumbent/supervisor
pairs and represented about 79 percent of the incumbents covered by
FES.  Table I.9 shows the gender and minority representation of the
37 occupations included in our study. 



                               Table I.9
                
                 Female and Minority Representation of
                the 37 Occupations Included in the Study


Female representation      High           Medium         Low
-------------------------  -------------  -------------  -------------
High                       Dental         Accounting     Dental
                           assistant      technician     hygiene

                           Medical clerk  Budget         Occupational
                                          analysis       therapist

                           Personnel      Nurse
                           clerical and
                           assistance

                                          Paralegal
                                          specialist

                                          Secretary

Medium                     Computer       Accounting     Auditing
                           operation

                           Equal          Computer       Cartographic
                           employment     specialist     technician
                           opportunity

                           Equal          Contracting    Industrial
                           opportunity                   hygiene
                           compliance

                           Mail and file  Diagnostic     Public
                                          radiologic     affairs
                                          technologist

                           Nursing        Housing
                           assistant      management


Low                        Border patrol  Plant          Agricultural
                           agent          protection     management
                                          and
                                          quarantine

                           Security       Police         Chemistry
                           guard

                                                         Forestry

                                                         Mechanical
                                                         engineering

                                                         Quality
                                                         assurance

                                                         Physical
                                                         science
                                                         technician

                                                         Safety and
                                                         occupational
                                                         health
                                                         management

                                                         Soil
                                                         conservation

                                                         Telecommunica
                                                         tions
----------------------------------------------------------------------
Source:  GAO analysis of data obtained from OPM. 


--------------------
\8 The 18 occupational series for which we received completed
questionnaires from less than 10 incumbent/supervisor pairs included
tax examining, computer clerk and assistant, security administration,
medical technologist, voucher examining, practical nurse, shipment
clerical and assistance, medical supply aide and technician, medical
instrument technician, equipment operator, architecture, mine safety
and health, dietician and nutritionist, veterinary medical science,
recreation specialist, language specialist, equal opportunity
assistance, and federal retirement benefits. 


   QUESTIONNAIRE VALIDATION
--------------------------------------------------------- Appendix I:5

We validated our job content questionnaire by using a second set of
desk audits.  To simplify selecting positions that represented a
broad range of grades, we combined our seven strata into three
groups:  high (GS-11 to 15), medium (GS-6 to 10), and low (GS-1 to
5).  We then scheduled interviews with incumbent/supervisor pairs,
which allowed us to complete desk audits that were distributed evenly
across the three GS grade ranges, the three selected geographical
locations, and the nine matrix cells.  Again, to ensure the
independence of the validation process, the contractor instructed the
job analysts not to review the incumbent/supervisor responses to the
questionnaire for any position before they completed a desk audit. 

Although we completed 100 desk audits, we validated the questionnaire
on the basis of the 78 positions that represented the 37 occupations
included in our analyses and for which the incumbent and supervisor
provided complete responses to the questionnaire.  For the 78
positions, we completed 24 desk audits for high, 35 for medium, and
19 for low graded positions; and 37 desk audits in Washington, D.C.;
21 in Los Angeles, CA; and 20 in Dayton/Cincinnati, OH.  Table I.10
shows the distribution of the 78 positions for which a desk audit was
completed by occupation and matrix cell. 



                                    Table I.10
                     
                      Distribution of Desk Audits Completed
                         According to Female and Minority
                      Representation for the 37 Occupations
                              Included in the Study


Fema
le
repr
esen
tati
on    High                  Medium                  Low                    Total
----  ----------  --------  ------------  --------  ----------  ------  ========
High  Dental             0  Accounting           0  Dental           8
      assistant             technician              hygiene

      Medical            3  Budget               2  Occupation       1
      clerk                 analysis                al
                                                    therapist

      Personnel          6  Nurse                0
      clerical
      and
      assistance

                            Paralegal            1
                            specialist

                            Secretary            3

================================================================================
      Subtotal           9  Subtotal             6  Subtotal         9        24

Medi  Computer           2  Accounting           2  Auditing         4
um    operation

      Equal              2  Computer             3  Cartograph       5
      employment            specialist              ic
      opportunit                                    technician
      y

      Equal              0  Contracting          3  Industrial       2
      opportunit                                    hygiene
      y
      compliance

      Mail and           2  Diagnostic           1  Public           4
      file                  radiologic              affairs
                            technologist

      Nursing            1  Housing              1
      assistant             management

================================================================================
      Subtotal           7  Subtotal            10  Subtotal        15        32

Low   Border             4  Plant                0  Agricultur       0
      patrol                protection              al
      agent                 and                     management
                            quarantine

      Security           3  Police               6  Chemistry        3
      guard

                                                    Forestry         0

                                                    Mechanical       3
                                                    engineerin
                                                    g

                                                    Quality          0
                                                    assurance

                                                    Physical         2
                                                    science
                                                    technician

                                                    Safety and       1
                                                    occupation
                                                    al
                                                    health
                                                    management

                                                    Soil             0
                                                    conservati
                                                    on

                                                    Telecommun       0
                                                    ications

================================================================================
      Subtotal           7  Subtotal             6  Subtotal         9        22

================================================================================
Tota                    23                      22                  33        78
l
--------------------------------------------------------------------------------
The resulting validity coefficient between GS grades estimated on the
basis of the 78 desk audits versus incumbent/supervisor questionnaire
responses was .80, thus meeting the goal we set when we designed the
study.  This is the only classification study we are aware of in
which desk audits were used to validate the questionnaire results. 
Table I.11 shows the validity coefficients between GS grades
estimated on the basis of desk audits versus the questionnaire
responses for incumbent/supervisor pairs, supervisors, and
incumbents. 



                               Table I.11
                
                    Validity Coefficients for Grades
                 Estimated on the Basis of the 78 Desk
                    Audits Versus the Questionnaire
                   Responses for Incumbent/Supervisor
                Pairs, Supervisors Only, and Incumbents
                                  Only

Source of questionnaire responses                 Validity coefficient
----------------------------------------  ----------------------------
Incumbent/supervisor pairs                                         .80
Supervisors                                                        .75
Incumbents                                                         .73
----------------------------------------------------------------------
Note:  While we validated our questionnaire on the basis of the
responses from incumbent/supervisor pairs, we reported the validity
coefficients for supervisors only and incumbents only for the purpose
of full disclosure. 

For the 37 occupations included in our analyses, we used loglinear
statistical techniques to analyze the odds of individual occupations
being overgraded or undergraded versus appropriately graded (1) in
relation to GS grades and (2) when the female or minority
representation of an occupation was high, medium, or low.  The
strength of this particular statistical approach was that multiple
variables could be analyzed simultaneously, thereby enabling us to
examine complex relationships in the data.  Appendix II provides more
detailed information on our loglinear methodology, the loglinear
models tested, and the results obtained. 


LOGLINEAR METHODOLOGY AND ANALYSIS
RESULTS
========================================================== Appendix II

This appendix provides additional technical detail on our analytical
approach.  It contains a general description of loglinear
methodology, describes the variables analyzed, and presents the
loglinear models tested and the results obtained in each analysis. 


   DATA ANALYSIS APPROACH
-------------------------------------------------------- Appendix II:1

We used loglinear analyses to examine the relationship between the
likelihood of being overgraded or undergraded and (1) the average GS
grade of the sampled incumbents by occupation and (2) female and
minority representation.\1 We first looked at the relationship
between the likelihood of being overgraded or undergraded and female
or minority representation without taking the effect of the average
GS grade into consideration.  For each analysis, we considered the
preferred model to be the simplest one that fit the data and could
not be significantly improved by more complex models.  The preferred
model included those components that had statistically significant
relationships with effects after we controlled for the influences of
other factors.  Hence, the estimates we obtained were net effects
determined after the association of each variable with all other
variables had been taken into account or statistically eliminated. 

On the basis of the preferred model, we estimated the direction and
magnitude of the relationships using odds and odds ratios.  The odds
indicated the likelihood that an outcome would occur given a
particular factor or combination of factors, and the odds ratios
indicated the size of the effect of the various factors on that
likelihood.  The more the odds ratio diverges from 1.0, the stronger
the relationship. 


--------------------
\1 We opted to use loglinear models rather than logistic regression
models because of the trichotomous nature (i.e., three
characteristics as opposed to being of a continuous nature) of the
dependent variable.  Logistic regression models could have been used
had we chosen to look separately at the two odds that we examined,
i.e., the odds of overgrading versus aptly grading and the odds of
undergrading versus aptly grading.  This would have allowed us to
control simultaneously for the average GS grade, gender, and minority
status had we wanted to determine how the relationship between job
content and GS grades assigned using FES varied on the basis of the
gender and minority status of incumbents.  Because our objective was
to determine whether the relationship varied on the basis of the
proportion of women and minorities in occupations, we chose the
simpler modeling strategy. 


   OCCUPATIONS INCLUDED IN OUR
   STUDY
-------------------------------------------------------- Appendix II:2

All of our analyses were based on the 37 occupations shown in table
II.1.  The table also indicates by occupation whether the female or
minority representation was high, medium, or low; the average GS
grade of the incumbents in the sample; whether the incumbents were
overgraded, aptly graded, or undergraded; and the odds of being
either overgraded or undergraded versus aptly graded.\2 For each
occupation or group of occupations, we derived the odds of being
overgraded versus aptly graded by dividing the number of incumbents
that were overgraded by the number aptly graded.  The odds of being
undergraded versus aptly graded were similarly calculated. 



                                                                      Table II.1
                                                       
                                                         Female and Minority Representation,
                                                          Average GS Grades, Observed Sample
                                                            Frequencies, and Odds of Being
                                                       Overgraded and Undergraded Versus Aptly
                                                          Graded for 37 Occupations Without
                                                               Controlling for GS Grade



                                                                                           Average
                                                                    GS                    GS grade                                      Over    Under
                                                            occupation                          in     Over    Aptly    Under  Tota   versus   versus
High      Medium    Low       High      Medium    Low        al series                      sample   graded   graded   graded     l  aptly\a  aptly\b
--------  --------  --------  --------  --------  --------  ----------  ----------------  --------  -------  -------  -------  ----  -------  -------
X                             X                                    203  Personnel             6.81       33       20       16    69     1.63     0.80
                                                                        clerical and
                                                                        assistance

X                             X                                    679  Medical clerk         4.45        4        3       15    22     1.29     4.43

X                             X                                    681  Dental assistant      5.12        2        6        9    17     0.38     1.46

X                                       X                          560  Budget analysis      11.98       84        1        1    86    56.33     1.00

X                                       X                          318  Secretary             5.40       20       24       38    82     0.84     1.57

X                                       X                          610  Nurse                11.20       16        2        2    20     6.60     1.00

X                                       X                          950  Paralegal            11.56       16        0        0    16    33.00     1.00
                                                                        specialist

X                                       X                          525  Accounting            5.62        6        2        5    13     2.60     2.20
                                                                        technician

X                                                 X                682  Dental hygiene        6.56        2        9       48    59     0.26     5.11

X                                                 X                631  Occupational         10.50        3        1        8    12     2.33     5.67
                                                                        therapist


Subtotal for occupations with high female representation
-----------------------------------------------------------------------------------------------------------------------------------------------------
=====================================================================================================================================================
                                                                                                        186       68      142   396     2.72     2.08

          X                   X                                    360  Equal                11.86       46        3        0    49    13.29     0.14
                                                                        opportunity
                                                                        compliance

          X                   X                                    260  Equal employment     12.26       41        0        1    42    83.00     3.00
                                                                        opportunity

          X                   X                                    332  Computer              7.93       36        3        2    41    10.43     0.71
                                                                        operations

          X                   X                                    621  Nursing               4.90        8        8       13    29     1.00     1.59
                                                                        assistant

          X                   X                                    305  Mail and file         4.20        2        5        3    10     0.45     0.64

          X                             X                          647  Diagnostic            5.94        5        6       23    34     0.85     3.62
                                                                        radiologic
                                                                        technologist

          X                             X                          334  Computer              9.67       26        3        4    33     7.57     1.29
                                                                        specialist

          X                             X                         1102  Contracting           8.57       17        7        4    28     2.33     0.60

          X                             X                          510  Accounting            9.20       10        2        3    15     4.20     1.40

          X                             X                         1173  Housing               5.45        1        5        5    11     0.27     1.00
                                                                        management

          X                                       X               1371  Cartographic          6.04       45       25       29    99     1.78     1.16
                                                                        technician

          X                                       X               1035  Public affairs       10.38       41        5        7    53     7.55     1.36

          X                                       X                511  Auditing             10.74       42        3        1    46    12.14     0.43

          X                                       X                690  Industrial            9.74       16        4        7    27     3.67     1.67
                                                                        hygiene


Subtotal for occupations with medium female representation
-----------------------------------------------------------------------------------------------------------------------------------------------------
=====================================================================================================================================================
                                                                                                        336       79      102   517     4.23     1.29

                    X         X                                   1896  Border patrol        10.75       85        4        3    92    19.00     0.78
                                                                        agent

                    X         X                                     85  Security guard        5.15       16        9       21    46     1.74     2.26

                    X                   X                           83  Police                5.34        4       16       38    58     0.27     2.33

                    X                   X                          436  Plant protection      9.13       14        2        0    16     5.80     0.20
                                                                        and
                                                                        quarantine

                    X                             X               1311  Physical science      5.55       31       30       19    80     1.03     0.64
                                                                        technician

                    X                             X                830  Mechanical           10.95       34        6        3    43     5.31     0.54
                                                                        engineering

                    X                             X               1910  Quality               9.95       17        2        3    22     7.00     1.40
                                                                        assurance

                    X                             X                460  Forestry              8.25        6        5        9    20     1.18     1.73

                    X                             X               1320  Chemistry            10.88       13        2        2    17     5.40     1.00

                    X                             X                457  Soil                  8.75       10        3        3    16     3.00     1.00
                                                                        conservation

                    X                             X                475  Agricultural          9.21        9        3        2    14     2.71     0.71
                                                                        management

                    X                             X                391  Telecommunicatio     10.64        8        0        3    11    17.00     7.00
                                                                        ns

                    X                             X                 18  Safety and           11.90        9        1        0    10     6.33     0.33
                                                                        occupational
                                                                        health
                                                                        management


Subtotal for occupations with low female representation
-----------------------------------------------------------------------------------------------------------------------------------------------------
=====================================================================================================================================================
                                                                                                        256       83      106   445     3.07     1.28

=====================================================================================================================================================
Total                                                                                         8.29      778      230      350  1,35     3.38     1.52
                                                                                                                                  8
-----------------------------------------------------------------------------------------------------------------------------------------------------
Note:  Odds were calculated after adding a small constant (0.5) to
all cell frequencies so that cells with zeros could be included in
the calculations. 

\a The odds of being overgraded versus aptly graded are equal to the
number of overgraded incumbents divided by the number of aptly graded
incumbents. 

\b The odds of being undergraded versus aptly graded are equal to the
number of undergraded incumbents divided by the number of aptly
graded incumbents. 

Source:  GAO analysis of questionnaire data. 


--------------------
\2 We defined occupations with high, medium, and low female
representation as those in which women represented 70 percent or
more, 31 to 69 percent, and 30 percent or less of incumbents,
respectively.  We defined occupations with high, medium, and low
minority representation as those in which minorities represented more
than 41 percent, 22 to 41 percent, or less than 22 percent of
incumbents, respectively.

On the basis of the average points derived from the questionnaires
completed by the incumbent and the supervisor, we determined the GS
grade for each position.  We compared that questionnaire grade with
the incumbent's actual GS grade and considered the position to be
aptly, or appropriately, graded if the questionnaire grade and the
actual grade were the same.  Otherwise, we considered positions to be
overgraded if the actual grade was higher than the questionnaire
grade and undergraded if the actual grade was lower than the
questionnaire grade. 


   RELATIONSHIP BETWEEN
   OVERGRADING/UNDERGRADING AND
   FEMALE OR MINORITY
   REPRESENTATION WITHOUT
   CONTROLLING FOR GS GRADE\3
-------------------------------------------------------- Appendix II:3

While we derived the study results from models fitted to table II.1,
we first considered the relationship between incumbents being
overgraded, aptly graded, or undergraded and female representation
(see table II.2).  It should be noted that the effect of the average
GS grade was not statistically eliminated, or controlled for, in this
comparison.  For high, medium, and low female representation,
overgraded and undergraded incumbents outnumbered those appropriately
graded.  We computed the odds as described above, and these odds
indicated the extent to which overgraded or undergraded incumbents
outnumbered aptly graded incumbents.  We computed ratios, sometimes
referred to as odds ratios, by dividing the odds of overgrading or
undergrading in one group of occupations by the corresponding odds in
another group.  For example, occupations with high female
representation were about 1.62 times more likely to be undergraded
rather than aptly graded when compared with occupations having medium
female representation (2.09 / 1.29 = 1.62).  The odds ratios shown in
the table indicate sizable differences in overgrading and
undergrading between occupations with high female representation and
those with medium representation but only slight differences between
those occupations with medium representation and those with low
representation. 



                                    Table II.2
                     
                     Relationship Between the Observed Sample
                      Frequencies and Female Representation
                         Without Controlling for GS Grade


Fem
ale
rep
res            Aptl
ent               y                   Odds of over               Odds of
ati  Overgrad  grad  Undergrad  Tota  versus aptly          under versus
on         ed    ed         ed     l        graded  Ratios  aptly graded  Ratios
---  --------  ----  ---------  ----  ------------  ------  ------------  ------
Hig       186    68        142   396          2.74    0.64          2.09    1.62
 h
Med       336    79        102   517          4.25    1.38          1.29    1.01
 ium
Low       256    83        106   445          3.08                  1.28
================================================================================
Tot       778   230        350  1,35
 al                                8
--------------------------------------------------------------------------------
Note:  The blank spaces in columns indicate that we did not compute
odds or odds ratios. 

Table II.2 indicates that all groups of occupations tended to be
overgraded versus aptly or undergraded.  The focus of our study was
determining whether occupations with high female representation
differed significantly from those with medium or low female
representation.  To determine whether the differences in the sample
data shown in table II.2 reflected "real" differences in the
population and not simply chance or sampling fluctuations, we fit the
models shown in the top section of table II.3 to the data shown in
table II.1. 

On the basis of the likelihood ratio chi-square values and degrees of
freedom associated with the different models we fit to the observed
data, the preferred model was the third one in the upper and lower
sections of the table.\4 The third model in the upper section of the
table indicated a pronounced tendency for incumbents of jobs with
high female representation to be undergraded.  The third model in the
lower section of the table indicated a pronounced tendency for the
incumbents of occupations with high minority representation to be
overgraded. 



                                    Table II.3
                     
                      Hierarchical Models Tested to Examine
                      Relationships Between Observed Sample
                       Frequencies and Female and Minority
                                  Representation


                                              Likelihood
Represen  Model                 Degrees of    ratio chi-  Probabilit     Pseudo-
tation    number                   freedom        square           y      R\2 \a
--------  --------  ----------  ----------  ------------  ----------  ----------
Female    F1        {F} {D}              4         37.18     < 0.001       0.000

          F2        {F} {D}              2          5.63        0.06       0.849
                    {FHD}

          F3        {F} {D}              3          8.57        0.04       0.770
                    {FHDU}

          F4        {F} {D}              0          0.00        1.00       1.000
                    {FD}

Minority  M1        {M} {D}              4         18.23     < 0.001       0.000

          M2        {M} {D}              2          0.98        0.61       0.946
                    {MHD}

          M3        {M} {D}              3          1.57        0.67       0.914
                    {MHDO}

          M4        {M} {D}              0          0.00        1.00       1.000
                    {MD}
--------------------------------------------------------------------------------
Legend

F = Female representation (high, medium, or low).
D = Difference between actual GS grade and questionnaire grade
(overgraded, aptly, or   undergraded).
M = Minority representation (high, medium, or low). 

Note:  The subscripts H, U, and O represent dummy variables, which
contrast (1) high female or minority representation with medium and
low, (2) undergraded with aptly and overgraded, and (3) overgraded
with aptly and undergraded, respectively. 

\a Pseudo-R\2 is calculated, following Goodman (1978), by subtracting
the L\2 for a given model from the L\2 for the baseline model of
independence (e.g., (37.18 - 5.63) / 37.18 = 0.849).

The result indicates the proportion of the variation in the dependent
variable (the change in GS grade or the odds of overgrading or
undergrading) that is accounted for by the factor or set of factors
included in the model. 

Table II.4 shows the results of fitting the models in the upper
section of table II.3 to the data in table II.2.  The odds ratios we
derived from the preferred model (F3) indicated that in the
population from which we drew our sample, incumbents of occupations
with high female representation were twice as likely (i.e., 2.02
times as likely as shown in the table) to be undergraded compared
with either aptly or overgraded, as incumbents of occupations with
low or medium female representation.  Again, we emphasize that the
effect of the average GS grade was not statistically eliminated, or
controlled for, when making this comparison. 



                                              Table II.4
                               
                                  Relationship Between the Expected
                                Frequencies and Female Representation
                                   Without Controlling for GS Grade


                                                                     Odds of           Odds of
                                         Aptl                           over             under
                 Female                     y                         versus            versus
                 representati  Overgrad  grad  Undergrad               aptly  Rati       aptly  Rati
Model            on                  ed    ed         ed   Total      graded    os      graded    os
---------------  ------------  --------  ----  ---------  ------  ----------  ----  ----------  ----
F1               High            226.87  67.0     102.06  396.00        3.38  1.00        1.52  1.00
                                            7
                 Medium          296.19  87.5     133.25  517.00        3.38  1.00        1.52  1.00
                                            6
                 Low             254.94  75.3     114.69  445.00        3.38              1.52
                                            7
====================================================================================================
                 Total           778.00  230.     350.00  1,358.
                                           00                 00
F2               High            186.00  68.0     142.00  396.00        2.74  0.75        2.09  1.63
                                            0
                 Medium          318.15  87.0     111.78  517.00        3.65  1.00        1.28  1.00
                                            6
                 Low             273.85  74.9      96.22  445.00        3.65              1.28
                                            4
====================================================================================================
                 Total           778.00  230.     350.00  1,358.
                                           00                 00
F3               High            196.04  57.9     142.00  396.00        3.38  1.00        2.45  2.02
                                            6
                 Medium          312.76  92.4     111.78  517.00        3.38  1.00        1.21  1.00
                                            6
                 Low             269.20  79.5      96.22  445.00        3.38              1.21
                                            8
====================================================================================================
                 Total           778.00  230.     350.00  1,358.
                                           00                 00
----------------------------------------------------------------------------------------------------
Note 1:  The blank spaces in columns indicate that we did not compute
odds or odds ratios. 

Note 2:  Due to rounding, expected frequencies do not always add to
the total. 

We also considered the relationship between incumbents being
overgraded, aptly graded, or undergraded and minority representation
(see table II.5).  It should be noted that the effect of the average
GS grade was not statistically eliminated, or controlled for, in this
comparison.  For high, medium, and low minority representation, the
number of overgraded and undergraded incumbents outnumbered those
appropriately graded.  The odds shown in the table indicate the
extent to which overgraded or undergraded incumbents outnumbered
aptly graded incumbents.  Occupations with high minority
representation were 1.43 times more likely to be overgraded rather
than aptly graded when compared with occupations having medium
minority representation (4.48 / 3.13 = 1.43).  The odds ratios shown
in table II.5 indicate pronounced differences in overgrading and
undergrading between occupations with high minority representation
and those with medium representation but only slight differences
between those occupations with medium representation and those with
low representation. 



                                    Table II.5
                     
                     Relationship Between the Observed Sample
                     Frequencies and Minority Representation
                         Without Controlling for GS Grade


Min
ori
ty
rep
res            Aptl
ent               y                   Odds of over               Odds of
ati  Overgrad  grad  Undergrad  Tota  versus aptly          under versus
on         ed    ed         ed     l        graded  Ratios  aptly graded  Ratios
---  --------  ----  ---------  ----  ------------  ------  ------------  ------
Hig       273    61         83   417          4.48    1.43          1.36    0.77
 h
Med       219    70        123   412          3.13    1.08          1.76    1.21
 ium
Low       286    99        144   529          2.89                  1.45
================================================================================
Tot       778   230        350  1,35
 al                                8
--------------------------------------------------------------------------------
Note:  The blank spaces in columns indicate where we did not compute
odds or odds ratios. 

Table II.5 indicates that all groups of occupations tend to be
overgraded versus aptly or undergraded.  The focus of our study was
determining whether occupations with high minority representation
differed significantly from those with medium or low minority
representation. 

Table II.6 shows the results of fitting the models in the lower
section of table II.3 to the data in table II.5.  The odds ratios we
derived from the expected frequencies indicate the extent of the
differences that existed in the population.  As previously noted, the
preferred model selected was model M3, which indicated that in the
population, incumbents of occupations with high minority
representation were 1.64 times more likely to be overgraded rather
than either aptly or undergraded.  The effect of the average GS grade
was not statistically eliminated, or controlled for, in this
comparison. 



                                              Table II.6
                               
                                  Relationship Between the Expected
                               Frequencies and Minority Representation
                                   Without Controlling for GS Grade


                                                                     Odds of           Odds of
                                         Aptl                           over             under
                 Minority                   y                         versus            versus
                 representati  Overgrad  grad  Undergrad               aptly  Rati       aptly  Rati
Model            on                  ed    ed         ed   Total      graded    os      graded    os
---------------  ------------  --------  ----  ---------  ------  ----------  ----  ----------  ----
M1               High            238.90  70.6     107.47  417.00        3.38  1.00        1.52  1.00
                                            3
                 Medium          236.04  69.7     106.19  412.00        3.38  1.00        1.52  1.00
                                            8
                 Low             303.06  89.5     136.34  529.00        3.38              1.52
                                            9
====================================================================================================
                 Total           778.00  230.     350.00  1,358.
                                           00                 00
M2               High            273.00  61.0      83.00  417.00        4.48  1.50        1.36  0.86
                                            0
                 Medium          221.11  73.9     116.90  412.00        2.99  1.00        1.58  1.00
                                            9
                 Low             283.89  95.0     150.10  529.00        2.99              1.58
                                            1
====================================================================================================
                 Total           778.00  230.     350.00  1,358.
                                           00                 00
M3               High            273.00  57.1      86.90  417.00        4.78  1.64        1.52  1.00
                                            0
                 Medium          221.11  75.7     115.20  412.00        2.92  1.00        1.52  1.00
                                            0
                 Low             283.89  97.2     147.91  529.00        2.92              1.52
                                            0
====================================================================================================
                 Total           778.00  230.     350.00  1,358.
                                           00                 00
----------------------------------------------------------------------------------------------------
Note 1:  The blank spaces in columns indicate that we did not compute
odds or odds ratios. 

Note 2:  Due to rounding, expected frequencies do not always add to
the total. 


--------------------
\3 All of the results reported in this section are provided for
illustrative purposes only. 

\4 The likelihood ratio chi-square indicates the relative fit of the
various models to the data in the tables. 


   RELATIONSHIP BETWEEN
   OVERGRADING/UNDERGRADING VERSUS
   GS GRADE AND FEMALE AND
   MINORITY REPRESENTATION
-------------------------------------------------------- Appendix II:4

As depicted in figures II.1 and II.2, we determined through
preliminary analyses that as the average GS grade increased (1) the
odds of overgrading increased significantly and (2) the odds of
undergrading decreased slightly.  The trend lines through the
scatterplots of points, or occupations, shown in figures II.1 and
II.2 were obtained from a loglinear model, which allowed the average
GS grade to be linearly related to the odds of overgrading and
undergrading.\5

   Figure II.1:  Odds of
   Overgrading by Average GS Grade
   Across 37 Occupations

   (See figure in printed
   edition.)

   Note:  Each plotted point
   represents one of the 37
   occupations in our study.

   (See figure in printed
   edition.)

   Figure II.2:  Odds of
   Undergrading by Average GS
   Grade Across 37 Occupations

   (See figure in printed
   edition.)

   Note:  Each plotted point
   represents one of the 37
   occupations in our study.

   (See figure in printed
   edition.)

Table II.7 shows the loglinear models fit to the data in table II.1
to arrive at the preferred model--model 11.  The first model is the
baseline and asserts that the odds of overgrading and undergrading do
not vary across the 37 occupations.  Model 2, which allows those odds
to vary linearly by average GS grade, improved significantly upon
model 1 and indicates that 67 percent of the variation between the
actual GS grades and grades calculated on the basis of the
questionnaire was attributable to the average GS grade.\6 The
difference between the pseudo-R\2 for model 11 and that for model 2
indicates that female and minority representation accounted for about
6 percent of the variation (.731 - .673 = .058).\7 Therefore, model
11, the preferred model indicates that 73 percent of the variation
between the actual GS grades and grades calculated on the basis of
the questionnaire was attributable to a combination of average GS
grade and female and minority representation.  The remaining 27
percent of the variation was not explained by the variables in our
study. 



                               Table II.7
                
                 Loglinear Models Tested to Examine the
                 Relationship Between the Frequencies,
                 the GS Grade, and Female and Minority
                             Representation

Mode                                        Degree  Likeliho
l                                             s of  od ratio
numb                                        freedo      chi-   Pseudo-
er    Models tested                              m  square\a    R\2 \b
----  ------------------------------------  ------  --------  --------
1     {O} {D}                                   72    698.33     0.000
2     {O} {GLD}                                 70    228.10     0.673
3     {O} {GLD} {FHD}                           68    214.64     0.693
4     {O} {GLD} {MHD}                           68    202.34     0.710
5     {O} {GLD} {FHD} {MHD}                     66    185.26     0.735
6     {O} {GLD} {FHD} {MHD} {FMD}               64    183.16     0.738
7     {O} {GLD} {FHD} {MHD} {MMD}               64    182.77     0.738
8     {O} {GLD} {FHD} {MHD} {FHMHD}             64    181.36     0.740
9     {O} {GLD} {FHD} {MHD} {FHGLD}             64    181.29     0.740
10    {O} {GLD} {FHD} {MHD} {MHGLD}             64    180.04     0.742
11    {O} {GLD} {FHDU} {MHDO}                   68    188.11     0.731
----------------------------------------------------------------------
Legend

O = Occupation (1 of 37 occupations covered by FES that were included
in our study).
D = Difference between actual GS grade and questionnaire grade
(overgraded, aptly, or undergraded).
G = Grade (GS-1 to 15).
F = Female representation (high, medium, or low).
M = Minority representation (high, medium, or low).

Subscript L indicates a linear constraint imposed upon the effect of
the GS grade on overgrading or undergrading.

Subscripts H and M represent dummy variables which contrast high
female or minority representation with medium and low representation,
and medium female or minority representation with high and low
representation, respectively.

Subscript U represents a dummy variable which contrasts undergraded
with aptly and overgraded.

Subscript O indicates overgraded with aptly and undergraded. 

\a The likelihood ratio chi-square (L\2 ) indicates the relative fit
of the various models to the data in the table. 

\b Pseudo-R\2 is calculated, following Goodman (1978), by subtracting
the L\2 for a given model from the L\2 for the baseline model of
independence (e.g., (698.33 - 228.10) / 698.33 = 0.673).  The result
indicates the proportion of the variation in the dependent variable
(the change in GS grade or the odds of overgrading or undergrading)
that is accounted for by the factor or set of factors included in the
model. 

Table II.8 shows the expected frequencies under model 11 and the odds
of overgrading and undergrading derived from them.  Across the 37
occupations included in our study, of the total 1,358 positions in
our sample, about 780 or 57 percent appeared to be overgraded, 352 or
26 percent appeared to be undergraded, and 232 or 17 percent appeared
to be aptly graded.\8

We recognize that, on the surface, these summary results could raise
questions about the overall accuracy of the FES classification
system.  We believe that our results should be viewed with caution in
this respect because we did not design our study to assess the
overall accuracy of the classification system.  Rather, our use of
nontraditional methods, i.e., the use of the primary standard rather
than occupation-specific standards on which to develop a job content
questionnaire coupled with the use of the questionnaire rather than
desk audits, and our sample selection methodology were designed to
examine the relative assignment of grades among groups of
occupations.  That is, our study was designed to assess whether there
were differences in the likelihood of overgrading or undergrading
among groups of occupations that included higher or lower proportions
of women and minorities. 

We validated our design for achieving this objective; we did not
validate our design for an objective of expressing an opinion on the
overall accuracy of the classification system.  Had we undertaken
such an assessment, we would have utilized a more extensive strategy
to validate the relationship between the questionnaire we developed
and the results of more traditional classification tools such as desk
audits, or indeed a heavier reliance directly on desk audits, which
is how classification accuracy studies are usually conducted. 

We also recognize that the overall extent of apparent overgrading or
undergrading identified may involve some measurement error.  However,
we have no reason to believe that such error would be more pronounced
for any particular group of occupations, for example, occupations
with high female representation compared with those with medium or
low representation.  Thus, we do not believe that our estimates of
the differences in odds of overgrading or undergrading for the groups
of occupations included in our analysis have been affected by any
possible measurement error.  Also, the likelihood of a position being
overgraded, rather than aptly graded increased as the incumbents' GS
grades increased.  However, the incumbents' grades had virtually no
effect on the likelihood that a position was undergraded versus aptly
graded.  Accordingly, in measuring the odds of overgrading among
those groups of occupations, we controlled for (statistically
eliminated the effect of) the grade level effect we observed.  The
remaining variation in the data indicated statistically significant
differences among the groups of occupations, and we report on those
results. 



                                                                      Table II.8
                                                       
                                                         Female and Minority Representation,
                                                       Average GS Grades, Expected Frequencies,
                                                        and Odds of Overgraded and Undergraded
                                                        Versus Aptly Graded for 37 Occupations



                                                                                        Average
                                                                                       GS grade                                         Over    Under
                                                                     GS occupational         in     Over    Aptly    Under            versus   versus
High      Medium    Low       High      Medium    Low                series              sample   graded   graded   graded    Total  aptly\a  aptly\b
--------  --------  --------  --------  --------  --------  -------  ----------------  --------  -------  -------  -------  -------  -------  -------
X                             X                                 203  Personnel             6.81    33.93    11.04    24.17       69     3.07     2.19
                                                                     clerical and
                                                                     assistance

X                             X                                 679  Medical clerk         4.45     4.64     4.88    12.63       22     0.95     2.59

X                             X                                 681  Dental assistant      5.12     4.75     3.57     8.83       17     1.33     2.47

X                                       X                       560  Budget analysis      11.98    75.78     4.13     6.24       86    18.35     1.51

X                                       X                       318  Secretary             5.40    13.94    19.94    48.27       82     0.70     2.42

X                                       X                       610  Nurse                11.20    16.67     1.34     2.14       20    12.44     1.60

X                                       X                       950  Paralegal            11.56    13.78     0.92     1.44       16    14.98     1.57
                                                                     specialist

X                                       X                       525  Accounting            5.62     2.46     3.16     7.53       13     0.78     2.38
                                                                     technician

X                                                 X             682  Dental hygiene        6.56    16.46    13.22    29.47       59     1.25     2.23

X                                                 X             631  Occupational         10.50     9.31     1.06     1.78       12     8.78     1.68
                                                                     therapist


Subtotal for occupations with high female representation
-----------------------------------------------------------------------------------------------------------------------------------------------------
=====================================================================================================================================================
                                                                                                  191.72    63.26   142.50      396     3.04     2.27

          X                   X                                 360  Equal                11.86    46.84     1.24     1.07       49    37.77     0.86
                                                                     opportunity
                                                                     compliance

          X                   X                                 260  Equal                12.26    40.53     0.88     0.74       42    46.06     0.84
                                                                     employment
                                                                     opportunity

          X                   X                                 332  Computer              7.93    29.40     5.49     6.27       41     5.36     1.14
                                                                     operations

          X                   X                                 621  Nursing               4.90     9.61     8.08    11.46       29     1.19     1.42
                                                                     assistant

          X                   X                                 305  Mail and file         4.20     2.56     3.05     4.54       10     0.84     1.49

          X                             X                       647  Diagnostic            5.94     9.66    10.57    13.92       34     0.91     1.32
                                                                     radiologic
                                                                     technologist

          X                             X                       334  Computer              9.67    24.66     4.23     4.27       33     5.83     1.01
                                                                     specialist

          X                             X                      1102  Contracting           8.57    17.38     5.15     5.62       28     3.37     1.09

          X                             X                       510  Accounting            9.20    10.50     2.27     2.37       15     4.63     1.04

          X                             X                      1173  Housing               5.45     2.59     3.62     4.94       11     0.72     1.36
                                                                     management

          X                                       X            1371  Cartographic          6.04    29.15    30.33    39.67       99     0.96     1.31
                                                                     technician

          X                                       X            1035  Public affairs       10.38    43.00     5.18     4.97       53     8.30     0.96

          X                                       X             511  Auditing             10.74    38.62     3.89     3.64       46     9.93     0.94

          X                                       X             690  Industrial            9.74    20.38     3.38     3.39       27     6.03     1.00
                                                                     hygiene


Subtotal for occupations with medium female representation
-----------------------------------------------------------------------------------------------------------------------------------------------------
=====================================================================================================================================================
                                                                                                  324.88    87.36   106.87      517     3.72     1.22

                    X         X                                1896  Border patrol        10.75    84.62     3.89     3.63       92    21.75     0.93
                                                                     agent

                    X         X                                  85  Security guard        5.15    16.62    12.34    17.19       46     1.35     1.39

                    X                   X                        83  Police                5.34    12.93    19.04    26.18       58     0.68     1.38

                    X                   X                       436  Plant protection      9.13    11.07     2.48     2.60       16     4.46     1.05
                                                                     and
                                                                     quarantine

                    X                             X            1311  Physical              5.55    19.43    25.79    34.93       80     0.75     1.35
                                                                     science
                                                                     technician

                    X                             X             830  Mechanical           10.95    36.74     3.34     3.07       43    11.00     0.92
                                                                     engineering

                    X                             X            1910  Quality               9.95    17.08     2.55     2.52       22     6.70     0.99
                                                                     assurance

                    X                             X             460  Forestry              8.25    11.62     4.03     4.50       20     2.88     1.12

                    X                             X            1320  Chemistry            10.88    14.52     1.37     1.26       17    10.60     0.92

                    X                             X             457  Soil                  8.75    10.34     2.80     3.02       16     3.69     1.08
                                                                     conservation

                    X                             X             475  Agricultural          9.21     9.83     2.12     2.21       14     4.68     1.04
                                                                     management

                    X                             X             391  Telecommunicatio     10.64     9.25     0.98     0.92       11     9.44     0.94
                                                                     ns

                    X                             X              18  Safety and           11.90     9.18     0.52     0.45       10    17.65     0.87
                                                                     occupational
                                                                     health
                                                                     management


Subtotal for occupations with low female representation
-----------------------------------------------------------------------------------------------------------------------------------------------------
=====================================================================================================================================================
                                                                                                  263.33    81.25   102.48      445     3.24     1.26

=====================================================================================================================================================
Total                                                                                      8.29   779.93   231.87   351.85  1,358\c     3.37     1.52
-----------------------------------------------------------------------------------------------------------------------------------------------------
\a The odds of being overgraded versus aptly graded are equal to the
number of overgraded incumbents divided by the number of aptly graded
incumbents. 

\b The odds of being undergraded versus aptly graded are equal to the
number of undergraded incumbents divided by the number of aptly
graded incumbents. 

\c Due to rounding, totals for overgraded, aptly graded, and
undergraded do not add to 1,358. 

Source:  GAO analysis of questionnaire data. 

Table II.9 provides coefficients that indicate the direction and
magnitude of the different effects included in model 11.  The table
shows that the relationship between the average GS grades of
occupations and high minority representation and the odds of
incumbents being overgraded was statistically significant, while only
high female representation was related in a significant way to the
odds of incumbents being undergraded. 

The odds ratio 1.64 tells us that as the average GS grade increased
across occupations by one grade, the odds of incumbents being
overgraded increased by a factor of 1.64; that is, the likelihood of
being overgraded in an occupation in which the average grade of
incumbents was GS-10 was 1.64 times as great as the likelihood of
being overgraded in an occupation in which the average grade was
GS-9.  Independent of that, occupations with high minority
representation were 2.18 times more likely to be overgraded than
occupations with low or medium minority representation.  Finally,
occupations with high female representation were 1.77 times more
likely to be undergraded as occupations with low or medium female
representation.  The coefficient for the GS grade effect on
undergrading was not significantly different from 1.0 (which
indicates no effect), and the z-value associated with it implies that
the effect can reasonably be due to chance.\9



                                    Table II.9
                     
                     Coefficients and Odds Ratios Describing
                     the Effects of the Average GS Grade and
                     High Female and Minority Representation
                         on Overgrading and Undergrading

                                                          Lower 95      Upper 95
                                                           percent       percent
                                                        confidence    confidence
          Coefficient\  Standard                Odds      interval      interval
Factor               a     error   Z-value   ratio\b      estimate      estimate
--------  ------------  --------  --------  --------  ------------  ------------
Effect on overgrading
--------------------------------------------------------------------------------
GS grade         0.497     0.038     13.24      1.64          1.53          1.77
High             0.780     0.153      5.10      2.18          1.62          2.94
 minority
 represe
 ntation

Effect on undergrading
--------------------------------------------------------------------------------
GS grade        -0.071     0.043     -1.65      0.93          0.86          1.01
High             0.570     0.145      3.94      1.77          1.33          2.35
 female
 represe
 ntation
--------------------------------------------------------------------------------
Note:  Coefficients, standard errors, and z-values are taken from the
Loglinear Program in SPSSx. 

\a Coefficients are logged coefficients and indicate how much the
natural logarithm of the odds of overgrading or undergrading differ
across GS grades or female and minority representation. 

\b Odds ratios are derived directly from coefficients by taking
antilogarithms.  They are more readily interpretable than
coefficients because they indicate how much the odds of overgrading
or undergrading increase when GS grade increases or when occupations
with high female or minority representation are compared with
occupations having low or medium female or minority representation. 



(See figure in printed edition.)Appendix III

--------------------
\5 We derived the estimated odds that define the trend lines in the
figures from maximum likelihood estimation procedures rather than the
more common generalized least squares procedures.  These estimated
odds that we plotted in the two figures take into consideration the
number of sampled incumbents in each occupation. 

\6 We determine whether one model significantly improves upon another
by comparing values of L\2 --the likelihood ratio chi-square--which
indicates the fit of the models to data or how well the expected
frequencies resulting from the models correspond to the observed or
sample frequencies.  Since the difference in L\2 values between model
1 and 2 is highly significant given the difference in degrees of
freedom between the two (i.e., 698.33 - 228.10 = 470.23 with 72 - 70
= 2 degrees of freedom), we would choose model 2 as the preferred
model of the two and conclude that the linear effect of the GS grade
(which is present in model 2 but not in model 1) is a significant
effect or one that cannot be attributed to sampling fluctuations or
chance.  Comparisons between other models involve similar
calculations and logic. 

\7 The effects of the average GS grade and the female and minority
representation operate largely independent of each other.  The effect
of female and minority representation would account for approximately
7 percent of the variation if introduced into the model before the GS
grade. 

\8 Due to rounding, the frequency totals for overgraded, undergraded,
and aptly graded positions do not add to 1,358. 

\9 Z-values are the ratios of coefficients to their standard errors. 
When z-values exceed + 1.96 or - 1.96, coefficients are statistically
significant at the 95 percent level of confidence. 


COMMENTS FROM THE OFFICE OF
PERSONNEL MANAGEMENT
========================================================== Appendix II

61-62. 



(See figure in printed edition.)



(See figure in printed edition.)



(See figure in printed edition.)


The following are GAO's supplemental comments on the Office of
Personnel Management's letter dated September 8, 1995. 

GAO COMMENTS

1.  OPM said that some findings in our study, such as the overgrading
and undergrading within the same occupation, were left largely
unexplained.  As noted in the text, the job content questionnaire was
designed and validated to achieve our review objective relative to
comparing groups of occupations, and we cannot attest to the
questionnaire's validity when used across GS grades within
occupations, for specific occupations, or for individual positions. 

2.  OPM said that several uninvestigated variables were mentioned in
our study, any one of which might account for some or all of the
differences between the study results and the agency classification
results.  As noted in the text, we reported that 73 percent of the
variation we found between actual GS grades and those we estimated on
the basis of the questionnaire was attributable to the average GS
grades and female or minority representation; the remaining 27
percent was not explained by the variables included in our study. 
Thus, we believe the variables in our study accounted for most of the
variation. 


MAJOR CONTRIBUTORS TO THIS REPORT
========================================================== Appendix IV

GENERAL GOVERNMENT DIVISION,
WASHINGTON, D.C. 

Larry H.  Endy, Assistant Director, Federal Management and
 Workforce Issues
Brenda J.  Bridges, Evaluator-in-Charge
Gregory H.  Wilmoth, Senior Social Science Analyst
Douglas M.  Sloane, Senior Social Science Analyst
Don D.  Allison, Senior Evaluator
Jennifer S.  Cruise, Senior Evaluator


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RELATED GAO PRODUCTS
=========================================================== Appendix 1

Pay Equity:  Experiences of Canada and the Province of Ontario
(GAO/GGD-94-27BR, Nov.  2, 1993). 

Pay Equity:  Washington State's Efforts to Address Comparable Worth
(GAO/GGD-92-87BR, July 1, 1992). 

Federal Pay:  Comparisons With the Private Sector by Job and Locality
(GAO/GGD-90-81FS, May 15, 1990). 

State Department:  Minorities and Women are Underrepresented in the
Foreign Service (GAO/NSIAD-89-146, June 26, 1989). 

Pay Equity:  Status of State Activities (GAO/GGD-86-141BR, Sept.  19,
1986). 

Description of Selected Nonfederal Job Evaluation Systems
(GAO/GGD-85-57, July 31, 1985). 

Comments on Report on Comparable Worth by the United States
Commission on Civil Rights (GAO/GGD-85-59, June 14, 1985). 

Options for Conducting a Pay Equity Study of Federal Pay and
Classification (GAO/GGD-85-37, Mar.  1, 1985). 

Distribution of Male and Female Employees in Four Federal
Classification Systems (GAO/GGD-85-20, Nov.  27, 1984). 

Description of Selected Systems for Classifying Federal Civilian
Positions and Personnel (GAO/GGD-84-90, July 13, 1984). 

Classification of Federal White-Collar Jobs Should Be Better
Controlled (GAO/FPCD-75-173, Dec.  4, 1975). 

*** End of document. ***