Public Schools: Comparison of Achievement Results for Students	 
Attending Privately Managed and Traditional Schools in Six Cities
(29-OCT-03, GAO-04-62). 					 
                                                                 
Over the last decade, a series of educational reforms have	 
increased opportunities for private companies to play a role in  
public education. For instance, school districts have sometimes  
looked to private companies to manage poorly performing schools. 
The accountability provisions of the No Child Left Behind Act of 
2001 may further increase such arrangements because schools that 
continuously fail to make adequate progress toward meeting state 
goals are eventually subject to fundamental restructuring by the 
state, which may include turning the operation of the school over
to a private company. GAO determined the prevalence of privately 
managed public schools and what could be learned about student	 
achievement in these schools from publicly available sources. To 
do so, GAO examined existing data on the number and location of  
privately managed schools and reviewed a variety of reports on	 
student achievement. In addition, GAO compared standardized test 
scores of students attending privately managed public schools	 
with scores of students attending similar traditional public	 
schools. GAO identified privately managed schools that had been  
in operation for four years or more in 6 large cities and matched
these schools with a group of traditional schools serving similar
students. GAO then analyzed student scores on state reading and  
math tests at selected grade levels, controlling for differences 
in student populations. 					 
-------------------------Indexing Terms------------------------- 
REPORTNUM:   GAO-04-62						        
    ACCNO:   A08785						        
  TITLE:     Public Schools: Comparison of Achievement Results for    
Students Attending Privately Managed and Traditional Schools in  
Six Cities							 
     DATE:   10/29/2003 
  SUBJECT:   Academic achievement				 
	     Education program evaluation			 
	     Educational research				 
	     Educational testing				 
	     Privatization					 
	     Public schools					 
	     School management and organization 		 
	     Cleveland (OH)					 
	     Denver (CO)					 
	     Detroit (MI)					 
	     Phoenix (AZ)					 
	     San Francisco (CA) 				 
	     St. Paul (MN)					 

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GAO-04-62

United States General Accounting Office

GAO Report to the Chairman, Committee on Education and the Workforce,
House of Representatives

October 2003

PUBLIC SCHOOLS

 Comparison of Achievement Results for Students Attending Privately Managed and
                       Traditional Schools in Six Cities

GAO-04-62

Highlights of GAO-04-62, a report to the Chairman, Committee on Education
and the Workforce, House of Representatives

Over the last decade, a series of educational reforms have increased
opportunities for private companies to play a role in public education.
For instance, school districts have sometimes looked to private companies
to manage poorly performing schools. The accountability provisions of the
No Child Left Behind Act of 2001 may further increase such arrangements
because schools that continuously fail to make adequate progress toward
meeting state goals are eventually subject to fundamental restructuring by
the state, which may include turning the operation of the school over to a
private company.

GAO determined the prevalence of privately managed public schools and what
could be learned about student achievement in these schools from publicly
available sources. To do so, GAO examined existing data on the number and
location of privately managed schools and reviewed a variety of reports on
student achievement. In addition, GAO compared standardized test scores of
students attending privately managed public schools with scores of
students attending similar traditional public schools. GAO identified
privately managed schools that had been in operation for four years or
more in 6 large cities and matched these schools with a group of
traditional schools serving similar students. GAO then analyzed student
scores on state reading and math tests at selected grade levels,
controlling for differences in student populations.

October 2003

PUBLIC SCHOOLS

Comparison of Achievement Results forStudents Attending Privately Managedand
Traditional Schools In Six Cities

The number of public schools managed by private companies has tripled in
the last 5 years according to data compiled by university researchers,
although such schools comprise less than 0.5 percent of all public
schools. In the 2002-03 school year, nearly 50 private companies managed
over 400 public schools nationwide. These companies managed schools in 25
states and the District of Columbia, with about one-half of the schools
located in Arizona and Michigan. Information on student achievement at
these schools was available in the form of state- or district-issued
school report cards and annual reports issued by the management companies.
Although these reports provided valuable descriptive information, they
were generally not designed to answer research questions about the
relative effectiveness of privately managed schools compared with
traditional schools in raising student achievement. Consequently, GAO
conducted test score analyses that provide further insight into student
achievement in these schools.

Location of Public Schools Operated by Private Management Companies in
School Year 2002-03

Sources: GAO analysis of Arizona State University data; copyright (c)
Corel Corp. All rights reserved (map).

GAO's analyses of student test scores in 6 cities yielded mixed results.
Scores for 5th grade students in Denver and San Francisco were
significantly higher in both reading and math in two privately managed
schools when compared with traditional schools serving similar students.
However, 4th grade scores in reading and math were significantly lower in
a privately managed public school in Cleveland, as were 5th grade scores
in two privately managed schools in St. Paul. In Detroit, where eight
privately managed schools were studied, reading and math scores of 5th
graders in privately managed schools were generally lower. In Phoenix, GAO
found no significant differences. GAO's results are limited to the schools
and grade levels examined and may not be indicative of performance at
other schools.

www.gao.gov/cgi-bin/getrpt?GAO-04-62.

To view the full product, including the scope and methodology, click on
the link above. For more information, contact Marnie Shaul at (202)
512-7215 or [email protected].

Contents

Letter

Results in Brief
Background
Number of Schools Managed by Education Management

Companies Is Increasing; Descriptive Information on Achievement Widely
Available

No Consistent Pattern of Differences in Scores on State Tests Found
between Public Schools Managed by Private Companies and Comparable,
Traditional Elementary Schools

Concluding Observations Agency Comments

                                       1

                                      3 4

                                       7

17 30 31

     Appendix I                   Scope and Methodology                    33 
                               Scope and School Selection                  33 
                              Measures and Analytic Methods                36 
                               Limitations of the Analysis                 39 
     Appendix II   Tables of Regression Results for Differences in     
                       Student Achievement Scores on State Assessments 

Appendix III 	Characteristics of Privately Managed Schools and Comparable
Traditional Public Schools in Detroit

         Appendix IV          GAO Contacts and Staff Acknowledgments       55 
                                           GAO Contacts                    55 
                                         Acknowledgments                   55 
     Related GAO Products                                                  56 

Tables

Table 1: State Assessment Schedules and Tests of Reading and Mathematics
through Fifth Grade in Six Cities in School Year 2001-02 6

Table 2: School Characteristics of the Privately Managed Schools and
Comparison Schools in Denver and San Francisco 18

Table 3: School Characteristics of the Privately Managed Schools

and Comparison Schools in Cleveland and St. Paul 23 Table 4: School
Characteristics of the Privately Managed School

and Comparison Schools in Phoenix 29 Table 5: Regression Results for
Differences in Student

Performance on State Assessments at the Privately

Managed and Comparison Schools in Denver 42 Table 6: Regression Results
for Differences in Student

Performance on State Assessments at the Privately

Managed and Comparison Schools in San Francisco 43 Table 7: Regression
Results for Differences in Student

Performance on State Assessments at the Privately

Managed and Comparison Schools in Cleveland 44 Table 8: Regression Results
for Differences in Student

Performance on State Assessments at the Privately

Managed School and Comparison Schools in St. Paul

(School A Comparison) 45 Table 9: Regression Results for Differences in
Student

Performance on State Assessments at the Privately

Managed School and Comparison Schools in St. Paul

(School B Comparison) 46 Table 10: Regression Results for Differences in
Student

Performance on State Assessments at the Privately

Managed and Comparison Schools in Phoenix 47 Table 11: Regression Results
for Differences in Student

Performance on State Reading Assessment at the Privately

Managed and Comparison Schools in Detroit 48 Table 12: Regression Results
for Differences in Student

Performance on State Math Assessment at the Privately

Managed and Comparison Schools in Detroit 51

Figures

Figure 1: Number of Public Schools Managed by Private

Companies from School Year 1998-99 through 2002-03 8 Figure 2: Location of
Public Schools Operated by Private Management Companies in School Year
2002-03 and Annual Number of States with Such Schools Since 1998-99 9

Figure 3: Number of Educational Management Companies from School Year
1998-99 through 2002-03 10 Figure 4: Test Score Section of a Report Card
for a Hypothetical School in Colorado for School Year 2002-03 13

Figure 5: Fifth Grade Reading Scores for the Privately Managed School and
Comparison Schools in Denver on the Colorado Student Assessment Program 19

Figure 6: Fifth Grade Reading and Math Scores for the Privately Managed
School and Comparison Schools in San Francisco on the Stanford-9
Achievement Test 21

Figure 7: Fourth Grade Reading Scores for the Privately Managed School and
Comparison Schools in Cleveland on the Ohio Proficiency Test 24

Figure 8: Fifth Grade Reading and Math Scores for the Privately Managed
Schools and Comparison Schools in St. Paul on the Minnesota Comprehensive
Assessment Program 25

Figure 9: Fourth Grade Reading Scores for Privately Managed and Comparison
Schools in Detroit on the Michigan Education Assessment Program 27

Figure 10. Fourth Grade Math Scores for Privately Managed and Comparison
Schools in Detroit on the Michigan Education Assessment Program 28

Figure 11: Fifth Grade Reading and Math Scores for the Privately Managed
School and Comparison Schools in Phoenix 30

Abbreviations

NCLBA No Child Left Behind Act of 2001
LEP limited English proficiency
OLS ordinary least squares

This is a work of the U.S. government and is not subject to copyright
protection in the United States. It may be reproduced and distributed in
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separately.

United States General Accounting Office Washington, DC 20548

October 29, 2003

The Honorable John A. Boehner
Chairman
Committee on Education and the Workforce
House of Representatives

Dear Mr. Chairman:

In the last decade, reports of failing schools and low student achievement
have given rise to a variety of educational reforms that have expanded
opportunities for private companies to play a role in public education. In
some cases, school districts have looked to private companies to manage
poorly performing schools with the expectation of improving scores on
state achievement tests. The accountability requirements of the No Child
Left Behind Act (NCLBA) of 2001 may further increase such arrangements
because schools that continuously fail to make adequate yearly progress
toward meeting state proficiency goals may be eventually subject to
fundamental restructuring by the state, including turning the operation of
the school over to a private management company.1

As the role of private companies in the management of public schools has
developed, interest in students' academic performance at these schools
has grown. In light of the expanding role for private companies in public
education, we agreed with your office to determine the prevalence of
public schools managed by private companies and to report on what can
be learned about student achievement in these schools from publicly
available information sources. In addition, we agreed to compare student
achievement in elementary schools operated by private companies in large
urban areas with student achievement in similar traditional elementary
schools.

To determine the prevalence of privately managed schools, we obtained
information from research organizations on the number and location of
public schools that have both instructional and noninstructional services
provided by private companies. We relied primarily on a 2002-03 annual
report compiled by Arizona State University that tracks nationwide growth

1Public Law 107-110, Jan. 8, 2002.

of for-profit educational management companies, the only such report of
its kind we found.2 We selectively verified data in that report with
information compiled by the National Center for Education Statistics, the
Center for Education Reform, the National Association of Charter School
Authorizers, and university researchers in Michigan and New Jersey. To
locate publicly available information on student achievement in privately
managed schools, we examined a variety of Internet Web sites, including
state, district, and the larger private management company sites. We also
reviewed studies conducted by the companies and by other researchers, as
well as performance reports issued by state and district school officials
to learn what has been reported about achievement at these schools.

To compare student achievement in public elementary schools operated by
private companies with that at similar traditional schools, we analyzed
individual student performance in specific grades on mandatory state tests
of reading and mathematics. We identified 14 public elementary schools in
larger urban areas across the country that had been continuously managed
by private companies since the 1998-99 school year. These schools, managed
by six private companies, were located in six cities: Cleveland, Ohio;
Denver, Colorado; Detroit, Michigan; Phoenix, Arizona; St. Paul,
Minnesota; and San Francisco, California. We matched each of the 14
schools with a set of 2 or more traditional public schools in the same
city that were similar in terms of grade span, enrollment, student race
and ethnicity, and the percentage of students with limited-English
proficiency, disabilities, and eligibility for the federally subsidized
free and reduced-price school lunch program. (See app. I for details on
the procedures used to match schools.) Using test scores for the school
years 2000-01 and 2001-02, we compared student scores in reading and math
at one grade level in each of the 14 privately managed schools with scores
of students in the same grade at the set of similar traditional schools.
We also analyzed changes in individual students' test scores over time in
the three cities where such data were available-Denver, Phoenix, and San
Francisco.

Our analyses controlled for differences in characteristics of students
attending the privately managed and traditional schools by using
demographic characteristics-such as those used in selecting similar

2Arizona State University researchers at the Education Policy Studies
Laboratory compile annual data on the number of companies and their
schools by school type, grade level, size of enrollment, year opened, and
location. See Alex Molnar, Glen Wilson, and Daniel Allen, Profiles of
For-Profit Education Management Companies 2002-2003, (Tempe: Arizona State
University, Jan. 2003).

Results in Brief

traditional schools-and student mobility to the extent that these data
were available for individual students. We use the word significant-as in
significantly higher or lower-throughout this report to mean statistical
significance at a 95-percent confidence level, not to refer to the
importance of the difference. Our study is constrained to varying degrees
by incomplete data for some locations and by the lack of information on
the reasons that individual students enrolled in these schools. In
addition, our findings about student performance are limited to the
particular grades in the privately managed and traditional schools we
studied and may not be indicative of other grades or schools. For this
reason, we do not identify the specific schools or the associated
management companies in our study by name. A detailed explanation of our
methodology, study limitations, and data verification procedures are found
in appendix I. We conducted our work from January to October 2003 in
accordance with generally accepted government auditing standards.

The number of public schools managed by private companies has tripled in
the last 5 years, according to data compiled by university researchers.
Nevertheless, only slightly more than 400 public schools were privately
managed in the 2002-03 school year, considerably less than 1 percent of
all public schools. Managed by 47 private companies, these schools were
located in 25 states and the District of Columbia, with about one-half
located in Arizona and Michigan. Descriptive information about achievement
at individual schools was widely available in the form of school report
cards that identified the proficiency levels or achievement scores of
students tested in the current year, relative to state standards and state
or district averages. Three company reports presented information on
changes in achievement over time for all their schools in one or more
states. While providing useful information on student achievement, these
reports were generally not designed to answer research questions about the
relative effectiveness of privately managed schools compared with
traditional schools.

Our analyses of scores on state reading and mathematics tests in selected
grades did not show a consistent pattern of superior student performance
between schools managed by private companies and demographically similar
traditional public schools in six cities. In two cities, Denver and San
Francisco, students at the privately managed schools had on average
significantly higher reading and mathematics scores than students at
similar traditional public schools. Students at these privately managed
schools also demonstrated greater academic gains over multiple years.
However, in two other cities, Cleveland and St. Paul, student scores in

Background

reading and math were significantly lower in schools managed by private
companies compared with similar traditional schools. In Detroit, results
were somewhat mixed, although scores tended to be lower in the privately
managed schools- reading scores were lower in 6 of the 8 privately managed
schools and math scores were lower in 7 of the 8 privately managed
schools, compared with similar traditional schools. In Phoenix, there were
no significant differences in either reading or math between students at
the two types of schools. Our results are limited to the schools and grade
levels examined and may not be indicative of performance at other schools.

The role of for-profit private companies in managing public schools is a
fairly recent phenomenon. Until the early 1990's, school districts
contracted with private companies largely to provide noninstructional
services, such as transportation, building maintenance, or school lunches.
By the 1994-95 school year, however, the role of private companies had
expanded to include instructional services in four school districts, as we
reported in a 1996 GAO study.3 These early decisions by school districts
to contract with private companies often followed years of frustration
with low student achievement in these schools. Since that time, the growth
of private for-profit educational management companies has been aided by
financial support from the business community and by the opportunities
states have offered for greater flexibility in the provision of education
services.

Private for-profit management companies supply a wide array of educational
and management services that may include providing the curriculum,
educational materials, and key staff as well as payroll processing,
busing, and building maintenance. The range and type of services vary by
company, and to some extent by school within the company, as some
companies have adapted their educational programs to the needs and
interests of local areas. According to a study of for-profit educational
management companies by Arizona State University, three-quarters of
schools operated by private for-profit management companies in school year
2002-03 served elementary grade students in kindergarten through fifth
grade and in some cases continued to serve students in higher grades. The
size of schools operated by private management

3See U.S. General Accounting Office, Private Management of Public Schools:
Early Experiences in Four School Districts, GAO/HEHS-96-3 (Washington,
D.C.: Apr. 19, 1996).

companies varied from an enrollment of fewer than 100 students to more
than 1,000 students, but averaged about 450. Several of the major
companies reportedly served a predominantly low-income, urban, and
minority student population.

Private companies operate both traditional public schools and public
charter schools. Some states or districts contract with companies to
manage traditional public schools-often poorly performing public schools.
These schools are generally subject to the same set of requirements that
govern traditional schools within the district. More commonly, companies
manage charter schools -public schools that operate under agreements that
exempt them from some state and district regulations but hold them
accountable for improving pupil outcomes. Enrollment in charter schools
generally is not limited to defined neighborhoods, but may draw from
larger geographic areas than is the case for most traditional schools and
must be open to all, without discrimination, up to enrollment limits. Like
traditional public schools, charter schools receive public funds and may
not charge tuition for regular school programs and services, but may
charge for before- and after-school services, extended day kindergarten,
or pre-kindergarten classes.

Public schools operated by private management companies, both traditional
and charter, are subject to requirements of the NCLBA, including expanded
testing requirements. Under this law, states must establish standards for
student achievement and goals for schools' performance. Results must be
measured every year by testing all students in each of elementary grades
three through five and middle school grades six through eight, starting in
school year 2005-06,4 and by assessing how schools have progressed in
terms of improving the performance of their students. Information from
these tests must be made available in annual reports that include the
performance of specific student subgroups, as defined by certain
demographic and other characteristics. During the school years covered in
our study, states were only required to test students in one elementary,
one middle school, and one high school grade. Table 1 identifies the
different state testing schedules and instruments for the elementary
grades in school year 2001-2002 in the cities where we made test score
comparisons.

4This requirement takes effect as long as specified amounts of federal
funding are provided for test administration. For more on this subject,
see U.S. General Accounting Office, Title

I: Characteristics of Tests Will Influence Expenses; Information Sharing
May Help States Realize Efficiencies, GAO-03-389 (Washington, D.C.: May 8,
2003).

Table 1: State Assessment Schedules and Tests of Reading and Mathematics
through Fifth Grade in Six Cities in School Year 2001-02

                                      Elementary 
                       City, state grades tested      State test administered 
                                           2 - 5 Stanford Achievement Test,   
                  Phoenix, Arizona               9th                          
                                                                      Edition 
                    San Francisco,         2 - 5 Stanford Achievement Test,   
                        California               9th                          
                                                                      Edition 
                  Denver, Colorado        3 - 5a  Colorado Student Assessment 
                                                                      Program 
                                               4         Michigan Educational 
                 Detroit, Michigan                                 Assessment 
                                                                      Program 
               St. Paul, Minnesota         3 & 5      Minnesota Comprehensive 
                                                                  Assessments 
                   Cleveland, Ohio             4        Ohio Proficiency Test 

Source: State education departments of the states shown.

aReading was tested in all three grades, but mathematics was tested only
in fifth grade.

Infrequent state testing is one of several factors that have hampered
efforts to evaluate the impact of privately managed public schools on
student achievement. To assess the impact of school management,
researchers must isolate the effects of private management from the
effects of other factors that could influence students' test scores, such
as school resources or student ability. Ideally, this would be
accomplished by randomly assigning students to either a privately managed
school or a traditionally managed school, resulting in two groups of
students generally equivalent except for the type of school assigned.
However, random assignment is rarely practical, and researchers usually
employ less scientifically rigorous methods to find a generally equivalent
comparison group. For instance, in some cases, schools may be matched on
schoolwide student demographic characteristics such as race or
socioeconomic status. When such characteristics can be obtained for
individual students in the study, validity is improved. In addition,
validity is further improved when the progress of students can be followed
over several years. However, if the data on individual student
characteristics are unreliable or unavailable, as has often been the case,
researchers experience difficulties developing valid comparison groups.
Similarly, if individual test scores are available only for one grade
rather than successive grades, researchers cannot reliably track the
progress of student groups over time and compare the gains made by the two
groups. In our 2002 report that examined research on schools managed by
some of the largest education management companies, we found that
insufficient

Number of Schools Managed by Education Management Companies Is Increasing;
Descriptive Information on Achievement Widely Available

rigorous research existed to clearly address the question of their impact
on student achievement.5 Part of the reason that so few rigorous studies
are available may stem from the difficulties inherent in this research.

Although the number of public schools operated by private, for-profit
management companies has risen rapidly in recent years, these schools
still comprise a very small proportion of all public schools nationwide.
Largely charter schools, the 417 privately managed schools were located in
25 states and the District of Columbia in school year 2002-03, with about
one-half in Arizona and Michigan. These schools were operated by 47
private management companies. Descriptive information about achievement in
these schools was widely available in the form of individual school report
cards that often provided comparisons with state or district averages, but
often not with similar traditional schools. Three management company
reports summarized achievement gains over time for all their schools in
one or more states, using various methodologies to illustrate student
performance. School and company reports provided useful information on
student achievement, but generally were not designed to answer research
questions about the effectiveness of privately managed schools compared
with traditional schools.

While Numbers Are Increasing, the Percentage of Public Schools Managed by
Private Companies Remains Small

In school year 2002-03, at least 417 public schools were operated by
private for-profit management companies, according to Arizona State
University researchers.6 This figure was three times greater than the
number of schools operated by private management companies just
4 years earlier, when there were only 135 schools, as shown in
figure 1. Over three-quarters of the 417 schools were charter schools, and
they comprised about 12 percent of charter schools nationwide. Despite
the sharp rise in the number of public schools operated by management
companies, they represented a small proportion of all charter and

5See U.S. General Accounting Office, Public Schools: Insufficient Research
to Determine Effectiveness of Selected Private Education Companies,
GAO-03-11 (Washington, D.C.: Oct. 29, 2002).

6Arizona State University researchers list only schools operated by
management companies that the researchers can positively identify as
for-profits, but additional schools and companies may exist that the
researchers cannot positively identify. The researchers count as a single
school the grades in one or more buildings that are under the supervision
of a single principal.

traditional schools in 2002-03. About one-half of 1 percent of all schools
nationwide were privately managed schools.

Figure 1: Number of Public Schools Managed by Private Companies from
School Year 1998-99 through 2002-03

Number of schools

500

                                      417

400

300

200

100

0 1998-99 1999-00 2000-01 2001-02 2002-03 School year

Source: GAO graphic of Arizona State University data.

Over the same 5 years, public schools operated by private management
companies have also become more geographically widespread, according to
data from the Arizona State University study. Figure 2 shows that in
school year 1998-99, private management companies operated public schools
in 15 states. By school year 2002-03, the companies had schools in 25
states and the District of Columbia, with about 48 percent of the
privately managed schools in Arizona and Michigan. Florida, Ohio, and
Pennsylvania also had large numbers of schools as indicated by the map in
figure 2, which shows the location of public schools operated by private
management companies in school year 2002-03.

Figure 2: Location of Public Schools Operated by Private Management
Companies in School Year 2002-03 and Annual Number of States with Such
Schools Since 1998-99

Sources: GAO analysis of Arizona State University data; copyright (c)
Corel Corp. All rights reserved (map).

The number of private management companies identified by the Arizona State
University researchers also increased over the same period, but the
companies varied greatly in terms of the number of schools they operated.
As shown in figure 3, the number of companies increased from 13 in school
year 1998-99 to 47 in school year 2002-03. Most of these companies were
founded in the decade of the 1990's, but since their founding, some
companies have been consolidated or have gone out of business and have
been succeeded by newly formed companies. In school year 2002-03, most of
the companies were small, operating 15 or fewer schools each. Five
medium-sized companies-Chancellor Beacon Academies; The Leona Group;
Mosaica Education, Inc.; National Heritage Academies; and White Hat
Management-operated from 21 to 44 schools each. The single largest
company, Edison Schools, operated 116 schools.

Figure 3: Number of Educational Management Companies from School Year
1998-99 through 2002-03

Number of companies 50

                                       47

40

30

20

10

0 1998-99 1999-00 2000-01 2001-02 2002-03 School year

Source: GAO graphic of Arizona State University data.

According to the Arizona Sate University report, 43 of the 47 companies
operating in school year 2002-03 managed only charter schools.7 Charter
schools have greater autonomy and decision-making ability in such areas as
purchasing and hiring compared with traditional schools that are generally
subject to district requirements, including labor agreements. Arizona
researchers noted that state charter school laws have provided
opportunities for private management that were not present earlier, and
Western Michigan University researchers indicated that the growth of
private educational management companies occurred soon after charter
schools reforms were enacted in that state. They explained that some
charter holders started their own private management companies and other
charter holders sought the acumen and financial resources of management
companies already established in the business.8

Individual School Reports Describe Achievement Levels, and Some Company
Reports Describe Gains Compared to State or District Averages

Two kinds of reports available to the public -school reports and company
reports - described student achievement at privately managed schools
relative to national, state, or district averages in school year 2002-03.
Referred to as school report cards, the detailed individual school reports
generally provided a snapshot of how well students attending the school
did in meeting state achievement standards for the year. These report
cards were issued by states, school districts, and by some of the larger
companies, like the Leona Group for its schools in Michigan.9 Often
available through the Internet, the report cards for individual schools
generally described results of state tests in terms of the proficiency
levels or achievement scores for the school overall, by grade level,
subject matter, or in some cases, minority group or other subgroup.10 Some
report cards also provided historical information on the school's
performance over several preceding years. School characteristics, such as
the size, demographics, staffing, and finances, were included in many
cases along with the proficiency levels or achievement scores. Figure 4 is
an example

7Most of the schools managed by two of the other companies were charter
schools, but less than one-third of the schools operated by Edison Schools
and Victory Schools, Inc., were charter schools.

8See Jerry Horn and Gary Miron, An Evaluation of the Michigan Charter
School Initiative: Performance, Accountability, and Impact, (Western
Michigan University: July 2000).

9Individual school reports are also available from GreatSchools.net and
from Standard & Poors for a limited number of schools.

10NCLBA requires that report cards issued by states and districts include
this information, but scores for very small subgroups may be withheld to
protect the privacy of individual students whose scores might otherwise be
inferred.

of the test score section of Colorado's school report card for a
hypothetical school.

Figure 4: Test Score Section of a Report Card for a Hypothetical School in
Colorado for School Year 2001-02

Source: GAO composite developed from Colorado's Department of Education's
Web site www.state.co.us/schools.

Note: The Colorado school report cards include an explanation of the
factors used to develop the school's overall academic performance in this
section.

As in Colorado, many school report cards compared results to the average
in the state or school district, which allowed parents to see how well
their children's school was doing-not just in relation to state standards
but also in relation to the performance of all other public schools in the
state or district. However, these report cards were primarily designed to
provide descriptive information for parents and to give an indication of
school performance, not to evaluate the relative effectiveness of one
school versus another. Report cards usually did not directly compare the
performance of one school against other similar schools, and when they
did, the comparison schools selected were, by necessity, matched at the
school level, rather than the individual student level.11 Thus,
differences in school performance at any particular grade might be due to
differences in the students in that grade, as the reports released by the
Leona Group warned, rather than due to factors related to the management
or educational strategies of the school. For this reason, report cards,
while useful to parents, are not the best source of information if the
goal is to evaluate the effectiveness of one school compared with another.

Company reports, a second source of school performance information, tended
to provide a summary of how well students at all the company's schools in
one or more states were doing over a period of several years. Generally
available through the Internet, reports from three companies- Mosaica
Education, Inc.; the National Heritage Academies; and Edison Schools -
emphasized broad patterns, such as gains in achievement test scores or
proficiency levels that were averaged across schools, grades, and subjects
tested. Our descriptions of the companies' findings are based on their
public reports and not on our independent review of their methodologies or
conclusions.

Both the Mosaica and National Heritage Academies reports compared student
performance to national norms or state averages. The Mosaica Education,
Inc., report summarized student gains on tests administered from the fall
of school year 1999-2000 through the spring of 2001-02 at its

11California compares each individual school's rating with the ratings for
a set of 100 other schools matched on certain demographic and other
characteristics. The comparison schools selected by the state are not
required to be within the same geographic area, so that, for example, a
school in San Francisco might be matched with a school in San Diego.
Colorado compares each individual school's rating with those of other
schools in the neighborhood that are selected for their geographic
proximity rather than specially matched for demographic and other
characteristics.

18 schools in 5 states and the District of Columbia.12 According to the
report, there was sustained growth in average achievement scores over
time, with an increase in the proportion of Mosaica students scoring as
well or better than the average student on a nationally normed test and a
commensurate decrease in the proportion scoring at or below the 25th
percentile. On the basis of these test results, the report stated that
about a third of Mosaica's students ranked in the top one-half of the
nation's students in school year 2001-02.

The National Heritage Academies report used individual student performance
on the state's achievement tests to compare two groups of students
attending the company's 22 schools in Michigan in school year
2000-01-veteran students who took the test at least 2 years after they
applied to the school and newcomers who took the test less than 2 years
after they applied.13 The study found a relationship between time
associated with the company's schools and higher performance, with veteran
students outperforming newcomers across all subjects and grades tested and
also outperforming state averages on 8 out of 10 tests. The report
cautioned, however, that such evidence is not proof of causation and that
some other factors not accounted for in the study might be responsible for
the results.

The Mosaica and National Heritage Academies reports both provided a broad
view of overall company performance that, along with school report cards,
could give parents more information on which to base their decisions about
their children's schooling. However, like school report cards, these two
company studies were not designed to more directly assess school
effectiveness. Neither company report included comparisons with students
at similar traditional schools or addressed the question of whether the
patterns of achievement that they identified might also be found in other
schools as well.

12See R. William Cash, Mosaica Education Annual Report: Testing Results
1998-2002 (WestEd: Nov. 2002).

13See Gary Wolfram, PhD, Making the (Better) Grade: A Detailed Statistical
Analysis of the Effect of National Heritage Academies on Student MEAP
Scores, undated, www.heritageacademies.com/hillsdale.pdf, (downloaded June
30, 2003). Because enrollment dates were not available, application dates
were used as a proxy for enrollment. Furthermore, because raw scores were
not available, the analysis was based on the proficiency levels attained,
ranging from 2 possible levels on the writing tests to 4 possible levels
on the social studies tests. Other than gender, demographic data also were
not available.

Edison's annual report for 2001-02 used a methodology that went further
toward assessing school effectiveness than other company reports we
examined.14 In addition to providing a summary of how well its students
were doing over time, Edison compared some of its schools with traditional
schools. Generally, the report summarized trends in performance at 94 of
Edison's 112 school sites in multiple states over several years, compared
to state and district averages.15 According to the report, most schools
had low levels of achievement at the time Edison assumed management, but
achievement levels subsequently increased at most of its school sites.
Trends were also provided for several subsets of its schools, including a
comparison of 66 of the 94 Edison schools that could be matched with 1,102
traditional schools on two demographic variables. Traditional schools
selected as matches were those considered similar in terms of the
percentages of students who were African-American and/or Hispanic and who
were eligible for the free and reduced-price school lunch program, an
indicator of low income.16 Edison compared the average scores of students
in Edison schools with average scores of students in the traditional
schools and found that its schools averaged gains that were about 2
percentage points or 3 percentiles higher per year than those of
traditional schools and that about 40 of its 66 schools outperformed the
traditional schools.

However, the Edison analysis was limited by the fact that it was conducted
using aggregated, school-level data and did not control for differences in
the individual students being compared.17 Edison noted that it has taken
steps to strengthen the way it evaluates the progress of its students and
schools by commissioning a study by RAND, a nonprofit research
organization that has evaluated educational reforms. The study began in

14See Fifth Annual Report on School Performance: 2001-2002 (Edison: Feb.
2003).

15The report explains that 18 schools were excluded due to lack of data
for two points in time. For the remaining 94 schools, trends were
calculated from various beginning dates through 2001-02. The beginning
dates varied by school, depending on when Edison assumed management, and
ranged from school year 1995-1996 to school year 2000-01.

16For the comparison, all traditional schools in a district were
considered similar and included if their enrollment was within 10
percentage points of the Edison school on both student characteristics. If
no traditional schools were that close, then they were considered similar
and included if their enrollment was within 10 percentage points on one
characteristic and 30 percentage points on the other characteristic.

17An Edison official told GAO that the company did not have access to
individual data on students at traditional public schools used for the
comparison, so it was not able to conduct such an analysis.

2000 and is scheduled for release in the summer of 2004. Where possible,
RAND plans to compare the scores of individual Edison students to those of
traditional public school students with similar characteristics.

No Consistent Pattern of Differences in Scores on State Tests Found
between Public Schools Managed by Private Companies and Comparable,
Traditional Elementary Schools

Differences in student performance on state assessments between privately
managed public schools and comparable, traditional public schools varied
by metropolitan areas for the grade levels in our study.18 Average student
scores were significantly higher in both reading and math for fifth
graders in 2 privately managed schools, 1 in Denver and 1 in San
Francisco, compared with similar traditional public schools, as were gains
over time when we examined a previous year's scores for these students.
However, fourth grade scores in the privately managed school in Cleveland
and fifth grade scores at 2 privately managed schools in St. Paul were
significantly lower compared with scores in the similar traditional
schools. In Detroit, average fifth grade reading scores were significantly
lower in 6 of the 8 privately managed schools, and math scores were lower
in all but 1 privately managed school. No significant differences in
reading or math scores were found between the privately managed school and
comparison schools in Phoenix.

Scores on State Tests Were Higher in Privately Managed Schools in Denver
and San Francisco

Average scores on state tests for fifth grade students attending privately
managed schools in Denver and San Francisco were significantly higher
compared with students attending similar, traditional public schools.
Table 2 shows the characteristics used in matching privately managed and
traditional schools in Denver and San Francisco and how the selected
schools compared on these characteristics.19 As shown, schools generally
had high proportions of minority and low-income students (as measured by
free/reduced-lunch program eligibility) and students with limited English
proficiency (LEP). For our test score analyses, we were able to

18The word significant is used in this section to refer to statistical
significance. Differences discussed are significant at the 95-percent
confidence level using ordinary least squares regression models. Due to
concerns about certain assumptions inherent in these models, we also ran
models using robust estimation procedures to calculate standard errors.
For all models, the robust procedures yielded almost identical results to
those of the ordinary least squares. See appendix I for further details.

19For brevity, we show percent minority in this and similar tables.
However, our matching process actually used various categories of
race/ethnicity, depending on the data available for the site, rather than
a single minority category. See appendix II for the exact categories used.

obtain data on characteristics shown in table 2 for individual students in
our study, as well as data on student mobility.20 We used these data in
the test score analyses to further control for student differences in the
grade level we studied. (See app. II, where tables 5 and 6 show detailed
results of these analyses.)

Table 2: School Characteristics of the Privately Managed Schools and
Comparison Schools in Denver and San Francisco

                 Privately                Percent  Percent            Percent 
                  managed/                free and special           
      City      traditional    Enrollment  reduced education Percent minority 
                                             lunch           LEP     
     Denver      Privately            665       76         8      27 
                  managed                                            
     Denver     Traditional           645       77         4      40 
     Denver     Traditional           638       52         7      25 
     Denver     Traditional           403       80         8      52 
     Denver     Traditional           394       76        15      23 
      San        Privately            506       68         4      40 
Francisco      managed                                            
      San       Traditional           474       96         9      51 
Francisco                                                         
      San                                                            
Francisco    Traditional           525       81        10      33 

Source: Common Core of Data school year 2000-01 and school districts.

As shown in figure 5, in Denver the average reading score of 572 for fifth
grade students in the privately managed public school is higher, compared
with the average of 557 for students in similar traditional public
schools. The average math score of 467 at the privately managed school is
also higher than the 440 average score in the comparison traditional
schools. For both reading and math, differences in scores remained
significantly higher after we controlled for factors representing
differences in the student populations.

20In these analyses, a student is considered mobile if he or she did not
attend the same school in the prior year.

Figure 5: Fifth Grade Reading Scores for the Privately Managed School and
Comparison Schools in Denver on the Colorado Student Assessment Program

                           Source: GAO data analysis.

Note: Percentiles are derived from analyses that control for differences
in student characteristics.

Figure 5 also shows the difference in reading performance, controlling for
other factors, between the typical student at the privately managed school
and the average student at the same grade level in the similar traditional
schools in Denver. The bell curve represents the distribution of combined
student scores in the traditional schools, with the lighter figure
representing the student scoring at about the 50th percentile. The shaded
figure represents the average student from the privately managed school.
Although this student's score is at about the 50th percentile in the
privately managed school, the same score would place him or her at about
the 60th percentile when compared against the scores of students in the
traditional schools. The difference in math scores suggests a similar
outcome-that is, the average student in the privately managed school

would score at about the 60th percentile in the comparison traditional
schools.21

In San Francisco, fifth grade reading scores averaged 636 for students in
the privately managed school and 627 for students in the comparison
traditional schools. Performance in mathematics of 640 was also higher for
fifth grade students at the privately managed school, compared with 623
for students in the similar traditional schools. (See fig. 6.) As in
Denver, these differences were significant when controlling for other
factors. This analysis suggests that an average student in the privately
managed school would likely exceed about 60 percent of students in the
traditional comparison schools in reading and about 65 percent of those
students in math.

21See appendix I for a further discussion of this effect size illustration
and additional analyses comparing the privately managed school in Denver
with different groupings of the comparison traditional schools.

Figure 6: Fifth Grade Reading and Math Scores for the Privately Managed
School and Comparison Schools in San Francisco on the Stanford-9
Achievement Test

Average score 700 600 500 400 300 200 100 0

636 640

                              Reading Mathematics

              Traditional public schools Privately managed school

Source: GAO data analysis.

In both Denver and San Francisco, we were able to examine student
performance over time, and our findings of achievement over time were
similar to the findings described above. Students attending the privately
managed schools showed significantly greater gains over time than the
students in the comparison traditional schools. Specifically, fifth-grader
students in our study who had attended their privately managed schools
since the third grade demonstrated significantly higher achievement gains
between grades 3 and 5 than did such students in the traditional
comparison schools.22

22Third grade scores were available only for reading in Denver; in San
Francisco both reading and mathematics were examined.

Scores on State Tests Were Lower in Privately Managed Schools in Cleveland
and St. Paul

Average scores on state tests for fourth grade students attending
privately managed schools in Cleveland and fifth grade students attending
privately managed schools in St. Paul were significantly lower compared
with scores of students attending similar traditional public schools.23
One privately managed school in Cleveland and 2 privately managed schools
in St. Paul were examined, and as in Denver and San Francisco, the schools
in our study from these cities were high minority and low-income schools.
Table 3 shows the characteristics used to match schools in Cleveland and
St. Paul and how the schools selected compared on these characteristics.
For our test score analyses in Cleveland, we were able to obtain data on
characteristics shown in table 3 for individual students in our study, as
well as data on student mobility.24 In St. Paul, we obtained data on all
characteristics shown in table 3 for individual students, except special
education.25 In addition, we were able to obtain data on limited English
proficiency. We used these data in the test score analyses for both cities
to further control for student differences in the grade level we studied.
(See app. II, where tables 7, 8, and 9 show detailed results of these
analyses.)

23See appendix I for a discussion of additional analyses comparing the
privately managed school in Cleveland and St. Paul with different
groupings of the comparison traditional schools.

24In Cleveland, no students in our study were designated as limited in
English proficiency.

25The special education data we received on individual students in St.
Paul were not complete and thus were not used in our analyses of
individual test scores.

Table 3: School Characteristics of the Privately Managed Schools and
Comparison Schools in Cleveland and St. Paul

                 Privately                Percent free    Percent     Percent 
                 managed/                          and    special    
     City       traditional    Enrollment      reduced   education   minority 
                                                 lunch               
Cleveland Privately managed        411           77             4 
Cleveland    Traditional           422           80            10 
Cleveland    Traditional           496           88             8 
Cleveland    Traditional           352           77            16 
Cleveland    Traditional           561           99             8 
St. Paul  Privately managed        116           70            12 
St. Paul     Traditional           386           46            12 
St. Paul     Traditional           484           48            12 
St. Paul     Traditional           223           71             9 
St. Paul     Traditional           348           59            10 
St. Paul  Privately managed        126           71            14 
St. Paul     Traditional           313           76            16 
St. Paul     Traditional           223           71             9 
St. Paul     Traditional           438           64            13 
St. Paul     Traditional           524           68            17 

Source: Common Core of Data school year 2000-01 and school districts.

Figure 7 shows average reading scores for the privately managed school in
Cleveland and its set of comparable schools. The average scores were
significantly lower for students attending the privately managed school in
both reading and math for the school years examined after controlling for
other factors. The magnitude of the difference in reading scores is shown
in the same figure 7. As can be seen in the figure, the score of the
average student in the fifth grade in the privately managed school falls
at about the 20th percentile when compared with student scores in the
comparison traditional schools. Similarly, the difference in math scores
implies that the average student in the privately managed school would
score at about the 20th percentile in the traditional comparison schools.

Figure 7: Fourth Grade Reading Scores for the Privately Managed School and
Comparison Schools in Cleveland on the Ohio Proficiency Test

Source: GAO data analysis. Note: Percentiles are derived from analyses
that control for differences in student characteristics.

In St. Paul, we studied 2 privately managed schools (labeled school A and
school B in figure 8) and used a different set of comparison traditional
schools for each privately managed school. The average scores in both
reading and math were significantly lower for students at both privately
managed schools studied compared with similar traditional schools.

Figure 8: Fifth Grade Reading and Math Scores for the Privately Managed
Schools and Comparison Schools in St. Paul on the Minnesota Comprehensive
Assessment Program

School A comparisons School B comparisons

Average score

1,600

1,469

1,406 1,400

1,200

1,000

800

600

400

200

0 Reading Mathematics Reading Mathematics

Traditional public schools

Privately managed school Source: GAO data analysis.

The differences for the first privately managed school suggest that an
average student at that school would score at about the 30th percentile in
reading and the 20th percentile in math if attending the comparison
traditional schools. The differences in scores at the second privately
managed school imply that the score of an average student would be at
about the 30th percentile in the comparison traditional schools in both
reading and math.

Scores on State Tests in Privately Managed Schools Varied in Detroit and
Were Similar to Traditional Schools in Phoenix

Average scores for fourth grade students in Detroit varied, but tended to
be lower in both reading and math for students attending privately managed
schools than for students attending similar traditional schools.26 As in
other locations, student populations in schools we studied in Detroit
tended to be minority and low income. (See app. III for other school
characteristics.) Except for race/ethnicity, we did not use individual
student demographic data in the Detroit test score analyses because the
demographic data we received on individual students did not appear to be
accurate. In spite of these missing data, we believe the analyses provide
useful information, given the degree of similarity among the matched
schools.

As shown in figure 9, reading scores were significantly lower for students
in six of the privately managed schools compared with students in similar
traditional schools in Detroit. The size of these differences generally
suggested that an average student attending the privately managed schools
would score at about the 30th percentile in the similar traditional
schools. In one comparison (labeled C in fig. 9), reading scores were
significantly higher in the privately managed school compared with similar
traditional schools. Students at this privately managed school would
likely perform at about the 70th percentile in the traditional schools.
For one other privately managed school (comparison B), differences in
scores were not significantly different.

26For Detroit schools, because of difficulties obtaining data and changes
in the test, we analyzed reading and math test scores for 1 school
year-2001-02.

Figure 9: Fourth Grade Reading Scores for Privately Managed and Comparison
Schools in Detroit on the Michigan Education Assessment Program

Average reading score 400 350 300 250 200 150 100 50 0

306 301 306 307

                               AaBbCaDaEa FaGaHa

Detroit public schools

Source: GAO data analysis.

Traditional public schools

Privately managed school

aRepresents a statistically significant difference at the 95-percent
confidence level.

bNot statistically significant at the 95-percent confidence level but
approaches significance (p<.06).

Note : There are two parts to this reading exam, story section and
information section. The reported reading scores are an average of the two
sections and are only for the 2002 school year.

Math scores followed a similar pattern, with student scores significantly
lower at 7 of the 8 privately managed schools when compared with similar
traditional schools. Scores for average students in the privately managed
school would range from about the 15th percentile to about the 35th
percentile in the traditional schools, depending on the particular set of
schools compared. In the one higher-performing privately managed school
(comparison B in fig. 10), an average student in this privately managed
school would score at the 70th percentile in similar traditional schools.

Figure 10. Fourth Grade Math Scores for Privately Managed and Comparison
Schools in Detroit on the Michigan Education Assessment Program

Average math score 600

541 538 532 538

500

400

300

200

100

0

Aa Detroit public schools

Source: GAO data analysis.

BaCaDaEa FaGaHa

Traditional public schools

Privately managed school

aRepresents a statistically significant difference at the 95-percent
confidence level.

In Phoenix, scores of fifth grade students at the privately managed school
did not differ significantly from scores at similar traditional schools.
As in the other locations studied, both the privately managed and similar
traditional schools had high percentages of minority and low-income
students. Table 4 shows the characteristics of the schools in our study in
Phoenix. For test score analyses, we were able to obtain reliable data for
minority status for individual students. Additionally, we obtained
reliable data on student mobility, and these were included in our
analysis. Data on special education and limited English proficiency for
individual students were not believed to be accurate and were not
included. Individual student data on free and reduced-lunch eligibility
were not available.

Table 4: School Characteristics of the Privately Managed School and
Comparison Schools in Phoenix

             Privately               Percent    Percent               Percent 
              managed/               free and   special              
    City    traditional   Enrollment  reduced     education Percent  minority 
                                       lunch                  LEP    
Phoenix   Privately         1,066         96          25       50 
              managed                                                
Phoenix  Traditional          913         81          19       42 
Phoenix  Traditional          682         97          15       48 
Phoenix  Traditional          544         92          20       39 
Phoenix  Traditional        1,138         97           9       49 

Source: Common Core of Data school year 2000-01 and state education
department.

Figure 11 shows average student scores for reading and math in the
privately managed school and in the comparison traditional schools for
Phoenix. Scores were not significantly different in either reading or
math. We also analyzed changes in reading and math scores between third
and fifth grade for those students who had tested in the same school in
both years. Again, we found no significant difference between students
attending the privately managed school and those attending traditional
schools.

Figure 11: Fifth Grade Reading and Math Scores for the Privately Managed
School and Comparison Schools in Phoenix

Average score

                                                700 600 500 400 300 200 100 0

                                623 629 627 627

                              Reading Mathematics

              Traditional public schools Privately managed school

Concluding Observations

Source: GAO data analysis.

As opportunities increase for parents to exercise choice in the public
education arena, information on school performance, such as that found in
school report cards produced by many states, becomes more important. Such
information can be useful to parents in making school choices by providing
a variety of information about schools, including how they are performing
in terms of students meeting state achievement standards or relative to
statewide averages.

However, educators and policymakers often want to know not only how well
schools are performing but also the factors that contribute to their high
or low performance so that successful strategies can be emulated.
Answering this kind of evaluative question requires a different kind of
methodology and more complex analyses to isolate the effects of the
particular strategies of interest-educational practices, management
techniques, and so on- from the many other factors that could affect
student achievement. Although not a comprehensive impact evaluation, our
study investigates the effect of school management by comparing

traditional and privately managed schools and by controlling for
differences in the characteristics of students attending the schools. In
this way, our study provides a different type of information than that
typically found in school report cards.

While our study explores the role of school management, it has certain
important limitations, as discussed earlier and in appendix I. Among these
are data issues commonly encountered by educational researchers, for
instance, lack of test score data for successive years and unreliable
demographic data for individual students in some sites. However, with the
implementation of NCLBA, more rigorous studies should be possible, as
annual testing of all grades is phased in and with expected improvements
in the quality of demographic data resulting from requirements to report
progress for various subpopulations of students, based on such
characteristics as race and low-income status.

Finally, our mixed results may be evidence of the complexity of the factor
under study. Our study analyzed differences between 2 categories of
schools, grouped by whether they were traditional, district-managed
schools or managed by a private company. However, these schools may have
differed in other ways not included in our study-for example curricula,
staff composition and qualifications, and funding levels-and these factors
may also have affected student achievement. Any of these factors or
combination of factors could account for the differences we found or may
have masked the effects of differences we otherwise would have found.

Agency Comments 	We provided a draft of this report to the Department of
Education for review and comment. Education's Executive Secretariat
confirmed that department officials had reviewed the draft and had no
comments.

We are sending a copy of this report to the Secretary of Education,
relevant congressional committees, appropriate parties associated with
schools in the study, and other interested parties. We will make copies
available to others upon request. In addition, the report will be
available at no charge on GAO's Web site at http://www.gao.gov.

If you or your staff have any questions about this report, please call me
at (202) 512-7215. See appendix IV for other staff acknowledgments.

Sincerely yours,

Marnie S. Shaul, Director Education, Workforce, and Income Security Issues

                       Appendix I: Scope and Methodology

To compare achievement of public elementary schools in large cities
operated by private management companies with similar traditional public
schools, we analyzed individual student scores on state assessments in
reading and mathematics. We matched each privately managed public school
with 2 to 4 traditional public schools located in the same city that were
similar in terms of size, grade span, and student characteristics. To
confirm the reasonableness of the matches, we spoke with principals in all
of the privately managed schools in our study and visited most of the
schools. We also spoke with principals and visited many of the traditional
schools selected. For selected grade levels, we compared the individual
student scores of students attending the privately managed schools with
those of students in the similar traditional public schools. We also
compared changes in individual student performance over time where such
data were available. This appendix describes the scope and school
selection, outcome measures and analytic methods, and the limitations of
the analysis.

Using available public information,1 we attempted to identify all
privately managed public elementary schools in large urban areas that had
been in continuous operation by the same management company since the
1998-99 school year.2 We defined a large urban area for this study as a
central city with a population of at least 400,000 in a standard
metropolitan statistical area with a population of at least 2,000,000. We
identified 17 public elementary schools managed by private companies
meeting these criteria.3 The 17 schools were located in Cleveland, Ohio;
Denver, Colorado; Detroit, Michigan; Phoenix, Arizona; St. Paul,
Minnesota; and San Francisco, California.

Scope and School Selection

1The most comprehensive source we found for this information was a report
done by Arizona State University. We selectively verified data in this
report with other sources, such as compilations done for the Center for
Education Reform and the National Association of Charter School
Authorizers.

2If an elementary school managed by a private company also included middle
or high school grades, the school was retained in the study if other
selection criteria were met.

3We identified schools in Washington, D.C., and Miami, Florida, that met
our selection criteria. We did not include Miami in this study because we
previously reported the results of a study of the privately managed school
at this site. See U.S. General Accounting Office,

Public Schools: Insufficient Research to Determine Effectiveness of
Selected Private Education Companies , GAO-03-11. (Washington, D.C.: Oct.
29, 2002). We did not include Washington, D.C., because we were concerned
about obtaining reliable data.

Appendix I: Scope and Methodology

We matched each of these privately managed schools with 2-4 similar
traditional public schools in the district where the privately managed
school was located.4 To select similar traditional public schools, we
employed a "total deviation" score procedure. For each public elementary
school in the defined public school district and the privately managed
school, we determined the following school characteristics: (1) racial and
ethnic percentages,5 (2) percent special education, (3) percent eligible
for free and reduced lunch, (4) percent limited-English proficient,6 and
(5) student enrollment. We calculated z-scores (the statistic that
indicates how far and in what direction the value deviates from its
distribution's mean, expressed in units of its distribution's standard
deviation) for each characteristic, and then calculated the absolute value
of the difference between the z-score of the privately managed school and
the z-score of each traditional public school on that characteristic. For
each school, we summed the absolute difference in z-scores into a total
deviation score. The total deviation score represents the sum of the
differences between the privately managed public school and the candidate
traditional public schools.

Traditional public schools were considered a close match if the total
deviation score divided by the number of characteristics for which we
computed z-scores was less than or equal to 1.0. A score less than or
equal to 1.0 indicates that the traditional school did not deviate from
the privately managed school by more than 1 standard deviation when
averaging across all variables considered in the match. For example, if 8
variables were used to calculate the total deviation score and the total
deviation score was 7.8, the amount that the candidate school deviated
from the privately managed school would be, on average, less than 1
standard deviation. All comparison schools selected for our analyses met
this criterion for a close match.

4In Phoenix, the Phoenix Unified High School District was used as the
district demarcation for drawing matching traditional public schools.

5The specific matching variables varied from city to city. If students in
a given racial or ethnic group comprised less than 10 percent of the
student population in the privately managed school and if students in that
racial or ethnic group comprised less than 10 percent of the student
population for the other schools in the district, excluding outliers, we
excluded that racial or ethnic group as a specific matching variable.

6We sought, but were not able to obtain for use in the matching process,
data on percentage of students with limited English proficiency for
schools in St. Paul and Detroit.

Appendix I: Scope and Methodology

After mathematically selecting close matches, we consulted with public
school district officials about the schools selected.7 These
considerations led to adjustments to our final selection of matches as
follows. In St. Paul, traditional public schools closely matching the
privately managed schools included magnet schools and neighborhood, that
is, attendance-zone, schools. The two "best" matching magnet schools and
the two "best" neighborhood schools were selected as matches for the
analysis. Similarly in Cleveland, traditional public schools closely
matching the privately managed schools included former magnet schools and
traditional neighborhood schools. For balance in matching, the two "best"
matching former magnet schools and two "best" matching neighborhood
schools were selected as matches for the analysis. In Denver, the five
closest matching schools were all located in a distinct neighborhood,
geographically distant from the privately managed school. In consultation
with local school district personnel, the two "best" matching schools from
this area and the two "best" matching schools from outside this area were
selected for the analysis. In San Francisco, one of the three traditional
school matches was discarded because it had a special teacher training
program, resulting in only two matches with the privately managed school.
In Detroit, the best three matching traditional schools were selected
except in one instance where one of the matching schools was discarded
because a subsequent site visit determined that the school had selection
criteria for attendance based upon prior achievement. In Phoenix, there
were 21 elementary school districts located in the city, and 13 of these
districts comprise the Unified Phoenix High School District. Since the
privately managed schools were located within the Unified Phoenix High
School District, we selected matches from among the 13 school districts in
the Unified Phoenix High School District using the "best" matching school
of each elementary school district as a pool from which we selected the
best four matches, each from a different school district.

Two privately managed schools in Phoenix and one privately managed school
in Cleveland were dropped from the analysis because no matching
traditional schools were found using our methodology. This resulted in a
total of 14 privately managed schools included in the study, 8 of which
were located in Detroit. Schools selected were managed by Designs for
Learning, Inc.; Edison Schools; The Leona Group; Mosaica Education, Inc.;
Schoolhouse; and White Hat Management.

7Phoenix had multiple school districts, so we consulted with state
officials.

Appendix I: Scope and Methodology

Measures and Analytic Methods

We used student reading and math scale scores on routinely administered
state assessments as measures of academic achievement. At the time of our
study, the most recent data available were for school year 2001-2002. Test
scores and student characteristic data were obtained from either the
school district or state education agency. We used a variety of approaches
to verify the accuracy of these data. In most cases, we verified data by
comparing a sample of the data received against school records examined at
the school site. In Detroit, data verification indicated student
low-income, special education, and mobility data provided by the state
were unreliable, and we decided not to use these data in our final
analyses. In Phoenix, data verification indicated that student
limited-English proficiency and special education data provided by the
state for the privately managed school were unreliable and this was
confirmed with diagnostic analysis. Therefore, we were unable to include
these control variables in our final analyses.

For each privately managed school and its set of matched, comparison
schools, we selected the highest elementary grade for which test scores
were available. We collected test score information for 2 school years,
2000-01 and 2001-02, except in Detroit where only 2001-02 scores were used
due to difficulties obtaining data and changes in the test given. For each
site, we compared reading and math student scores in the privately managed
school(s) with the scores of same-grade students in the set of matched,
comparison schools. The scores for the 2000-01 and 2001-02 school years
were combined in the analysis.8 In addition, in three locations where
testing occurred more frequently, Denver, Phoenix, and San Francisco, we
obtained third grade scores for students who had taken the state
assessment in the same school and examined the difference in scores over
time.

For each site, we conducted multivariate ordinary least squares (OLS)
regression analysis to quantify differences in student achievement while
controlling for school type and student characteristics. Specific
independent variables included in the regression model were as follows:

o  	School type, with the traditional public school being given a value of
1 and the privately managed school a value of 0.

8Diagnostic analysis determined that school year was not related to
achievement scores in all sites except for reading scores in San
Francisco.

Appendix I: Scope and Methodology

o  	Mobility, with a value of 1 given to students not attending for 2
years the same school at which he or she took the state assessment.

o  	Limited English proficiency (LEP), with a value of 1 given if the
child was designated as limited-English proficient.9

o  	Special education, with a value of 1 given if the student was enrolled
in special education.10

o  	Low-income, with a value of 1 indicating the student was eligible for
free or reduced lunch.11

o  	Race and ethnicity, with a value of 1 given for the child's
appropriate minority racial/ethnic identity. Each child was placed in only
one racial category, and the number of racial categories used varied from
place to place. When numbers for a particular racial group in a city were
small, they were combined collectively as "other minority." (Specific
racial and ethnic identities employed in each city are set out in the
results in app. II.)

Student achievement on reading and mathematics were analyzed separately
for each privately managed public school with its set of matched schools.
The regression formula was:

Assessment Scorei = b1i + b2iSchool Type + b3iMobility + b4iLEP +

5iSpecial Education + b6iLow-income + b7iRace/Ethnicity + ei

where, (1) i is the individual student, (2) low-income is determined by
eligibility for free and/or reduced lunch, and (3) race and ethnicity are
distinct codes dependent upon the geographical area.

We also performed analyses on different groupings of the comparison
schools in Denver, Cleveland, and St. Paul. In Denver, 2 of our matched
schools were in a distinct neighborhood that school district personnel

9There are degrees of LEP; however, the data did not allow us to
differentiate the degree of limitation.

10There are degrees of disability; however, the data did not allow us to
differentiate for the degree or type of disability.

11In cities where both free and reduced-lunch variables were provided, the
analysis considered them separately.

Appendix I: Scope and Methodology

believed might be atypical; in Cleveland and St. Paul several of the
matched schools were magnet or former magnet schools. We re-analyzed the
data in each of these cities using these groupings as factors. The overall
results were unchanged, with the exception that in Denver, reading scores
were not significantly different when the privately managed school was
compared with the 2 schools not in the distinct neighborhood.

In Denver, San Francisco, and Phoenix, for the students in the grades we
analyzed, we also obtained the prior years' reading scores if the student
took the test in the same school. For this analysis, the regression
formula used the difference between reading scores in the highest
elementary grade and that of 2 years earlier as the dependent variable.
The independent variables were similar to those employed in the cross
sectional analysis with the exception that the reading/mathematics score
for the period 2 years earlier was also included as an independent
variable. The regression formula was:

Difference in Scorei = b1i + b2iSchool Type + b3iMobility + b4iLEP +

5iSpecial Education + b6iLow-income + b7iRace/Ethnicity +

8i

Assessment Score 2 Years Earlier + ei .

In conducting these analyses, we performed certain diagnostic and analytic
tests to confirm both the appropriateness of aggregating categories in our
analyses and the reasonableness of assumptions pertaining to normality and
homogeneity of variance. In addition, we determined the extent of missing
data and performed sensitivity analyses to assess the effect on our
results. We determined that missing case level data had a negligible
effect on our results.

To illustrate the magnitude of differences found, we computed effect sizes
based on standardized mean differences. Using the OLS regression results,
we divided the unstandardized coefficient associated with school type by
the pooled standard deviation to obtain z-scores for average students in
the privately managed and traditional schools. The reported percentile was
the area of the normal curve associated with the z-scores.

Tables 5-12 in appendix II list the regression results and independent
variables included in our analyses. The size and significance of the
differences we report were derived from OLS regression models. We obtained
results that were almost identical to the OLS results when we

Appendix I: Scope and Methodology

Limitations of the Analysis

used robust estimation procedures to calculate the standard errors
associated with the estimated differences. We also considered robust
regression models that allowed for the clustering, and lack of
independence, of students within schools. These models yielded somewhat
fewer differences that were statistically significant at the 95-percent
confidence level. We do not focus our reporting on the results of the
models that account for clustering, however, since the statistical
properties and validity of such models when applied to data with a very
small number of clusters (in this case, 3 to 5 schools) is questionable.12
However, changes to significance levels of the school type coefficients
due to robust standard errors and robust standard errors with clustering
are noted in appendix II.

The findings in this study are subject to typical limitations found in
quasi-experimental designs. We examined the highest elementary grades
tested for school years 2000-01 and 2001-02, and student achievement in
these grades and years may not be indicative of student achievement in
other grades and years in those schools. In addition, our matching process
may not have produced equivalent groups for comparison. We mitigated this
potential problem by using individual student characteristics in our
analyses. However, reliable and complete student demographic data were not
available in all sites, which resulted in the elimination of important
factors from the model in several sites. In addition, other factors such
as student ability, prior achievement, operating environment, reasons
students enrolled in privately managed schools, and parental involvement,
may be related to student achievement and are not accounted for in the
study. Finally, our examination of student performance over time, that is,
changes in achievement between grades, also has some limitations. First,
the data allowed a study of achievement over time in only 3 of the 6
sites. In addition, the analyses included only students who continuously
attended the school over the time period studied, and this in some cases
eliminated more than half of the subjects from the analyses. We were

12See Jeffrey M. Wooldridge, Econometric Analysis of Cross Section and
Panel Data (Cambridge: MIT Press, 2002), p.135.

Appendix I: Scope and Methodology

unable to determine whether those students who remained in the school for
this period were different in some important way from those who left.

Appendix II: Tables of Regression Results for Differences in Student Achievement
Scores on State Assessments

Tables 5-12 in this appendix show the variables used in the OLS regression
models and the results of those analyses. The results are presented
separately by city and for each privately managed school and its
particular set of matching traditional schools, with reading and math
presented within the same table in all cases, except Detroit. The number
of observations, shown as N, is the total of the observations in the
privately managed school and its set of comparison schools used in each
regression analysis.

We also ran similar regression analyses using robust estimation procedures
with and without clustering, as discussed in appendix I. In most cases,
effects of school type remained significant at the 95-percent confidence
level. Exceptions are indicated by table notes.

Appendix II: Tables of Regression Results for Differences in Student
Achievement Scores on State Assessments

Table 5: Regression Results for Differences in Student Performance on
State Assessments at the Privately Managed and Comparison Schools in
Denver Denver

                          Dependent variable: reading

N = 703

          F = 22.112 significance .000 Dependent variable: mathematics

                 Independent variable Coefficient Standard error Significance 
                             Constant                  630.8 8.9 
                   Traditional school                  -13.2 5.3        .014a 
                             Mobility                  -15.7 4.8         .001 
                    Special education                  -60.3 6.6         .000 
          Limited English proficiency                  -38.9 5.9         .000 
                  Free lunch eligible                  -17.7 5.2         .001 
               Reduced lunch eligible                    0.6 6.8         .932 
                     African American                  -36.1 7.6         .000 
                               Latino                  -24.4 8.3         .003 
                       Other minority                 -35.8 16.3         .028 

N = 704

      F = 22.120 significance .000                           
          Independent variable          Coefficient Standard Significance 
                                                       error 
                Constant                          521.6 10.3 
           Traditional school                      -24.0 6.2        .000a 
                Mobility                           -14.4 5.5         .009 
           Special education                       -81.9 7.5         .000 
      Limited English proficiency                  -20.7 6.8         .002 
          Free lunch eligible                      -19.5 6.0         .001 
         Reduced lunch eligible                      3.9 7.9         .625 
            African American                       -34.1 8.6         .000 
                 Latino                            -24.1 9.5         .011 
             Other minority                        -1.9 18.7         .921 

Source: GAO data analysis.

aUsing robust standard error procedures with clustering, the effect of
school type approaches but does not reach significance at the 95-percent
confidence level. (p = 0.06 for reading; p = 0.09 for math.)

Appendix II: Tables of Regression Results for Differences in Student
Achievement Scores on State Assessments

Table 6: Regression Results for Differences in Student Performance on
State Assessments at the Privately Managed and Comparison Schools in San
Francisco San Francisco

                          Dependent variable: reading

N = 388

          F = 6.158 significance .000 Dependent variable: mathematics

                 Independent variable Coefficient Standard error Significance 
                             Constant       651.9            7.1 
                   Traditional school        -7.8            3.4        .022a 
                             Mobility       -12.7            5.9         .031 
                    Special education       -18.5            7.9         .019 
          Limited English proficiency       -19.5            3.8         .000 
                  Free lunch eligible        -3.5            3.8         .362 
               Reduced lunch eligible         2.6            6.3         .684 
                     African American       -17.8            7.6         .020 
                               Latino         1.7            7.3         .815 
                                Asian        -8.9            7.5         .237 
                       Other minority       -17.3            8.9         .052 

                N = 394                                       
      F = 7.666 significance .000                             
          Independent variable     Coefficient Standard error Significance 
                Constant                            658.0 7.1 
           Traditional school                       -13.3 3.3         .000 
                Mobility                            -14.5 5.8         .013 
           Special education                         -7.4 7.8         .341 
      Limited English proficiency                   -12.0 3.8         .002 
          Free lunch eligible                        -4.5 3.7         .231 
         Reduced lunch eligible                      -1.8 6.2         .769 
            African American                        -27.3 7.5         .000 
                 Latino                              -5.3 7.2         .467 
                 Asian                               -7.7 7.4         .302 
             Other minority                         -19.6 8.7         .026 

Source: GAO data analysis.

aUsing robust procedures with clustering, the effect of school type is no
longer significant at the 95-percent confidence level.

Appendix II: Tables of Regression Results for Differences in Student
Achievement Scores on State Assessments

  Table 7: Regression Results for Differences in Student Performance on State
    Assessments at the Privately Managed and Comparison Schools in Cleveland

Cleveland

                          Dependent variable: reading

N = 631

                          F = 18.454 significance .000

             Independent variable   Coefficient  Standard error  Significance 
                         Constant         192.7             5.7 
               Traditional school          15.6             2.1          .000 
                         Mobility           1.1             1.6          .496 
                Special education         -17.1             2.6          .000 
              Free lunch eligible          -0.4             1.7          .815 
           Reduced lunch eligible           3.9             3.2          .233 
                         Minority           0.8             5.1          .876 

Dependent variable: mathematics

N = 650

                          F = 19.289 significance .000

                Independent variable  Coefficient Standard error Significance 
                            Constant        204.8            8.2 
                  Traditional school         24.7            3.0         .000 
                            Mobility         -1.4            2.3         .551 
                   Special education        -19.3            3.6         .000 
                 Free lunch eligible         -2.8            2.4         .250 
              Reduced lunch eligible          2.6            4.5         .568 
                            Minority        -17.5            7.4         .018 
          Source: GAO data analysis.                             

Appendix II: Tables of Regression Results for Differences in Student
Achievement Scores on State Assessments

Table 8: Regression Results for Differences in Student Performance on
State Assessments at the Privately Managed School and Comparison Schools
in St. Paul (School A Comparison) St. Paul

                          Dependent variable: reading

N = 459

          F = 41.904 significance .000 Dependent variable: mathematics

                 Independent variable Coefficient Standard error Significance 
                             Constant     1,478.6           50.7 
                   Traditional School       128.3           49.1         .009 
          Limited English proficiency      -160.1           33.8         .000 
          Free/reduced lunch eligible      -114.3           23.2         .000 
                     African American      -149.5           25.8         .000 
                       Other minority       -41.9           31.9         .191 

N = 452

  F = 34.238 significance .000 Independent variable Coefficient Standard error
                                  Significance

Constant 1,368.4 51.1

                       Traditional school 185.3 49.6 .000

         Limited English proficiency       -98.8        34.6          .004 
         Free/reduced lunch eligible       -112.8       23.4          .000 
              African American             -157.7       26.1          .000 
               Other minority              -24.6        32.4          .448 
         Source: GAO data analysis.                             

Note: Special education data were available for only one school year and
so were not included in the final analyses. Diagnostic analyses were run
for the one year that special education data were available to test for
the effects of including special education in the model. When special
education was included, school type remained significant at the 95-percent
confidence level.

Appendix II: Tables of Regression Results for Differences in Student
Achievement Scores on State Assessments

Table 9: Regression Results for Differences in Student Performance on
State Assessments at the Privately Managed School and Comparison Schools
in St. Paul (School B Comparison) St. Paul

                          Dependent variable: reading

N = 494

          F = 22.061 significance .000 Dependent variable: mathematics

                 Independent variable Coefficient Standard error Significance 
                             Constant     1,415.9           36.1 
                   Traditional school        90.5           33.5         .007 
          Limited English proficiency      -161.3           25.1         .000 
          Free/reduced lunch eligible       -54.6           19.3         .005 
                     African American       -86.0           22.8         .000 
                       Other minority        14.6           28.4         .607 

N = 474

  F = 18.883 significance .000 Independent variable Coefficient Standard error
                                  Significance

Constant 1,343.0 33.8

                       Traditional school 103.3 31.7 .001

         Limited English proficiency       -84.6        22.6          .000 
         Free/reduced lunch eligible       -42.0        17.9          .020 
              African American             -110.9       21.3          .000 
               Other minority               10.2        25.5          .690 
         Source: GAO data analysis.                             

Note: Special education data were available for only one school year and
so were not included in the final analyses. Diagnostic analyses were run
for the one year that special education data were available to test for
the effects of including special education in the model. When special
education was included, school type remained significant at the 95-percent
confidence level.

Appendix II: Tables of Regression Results for Differences in Student
Achievement Scores on State Assessments

Table 10: Regression Results for Differences in Student Performance on
State Assessments at the Privately Managed and Comparison Schools in
Phoenix Phoenix

                          Dependent variable: reading

N = 838

          F = 16.304 significance .000 Dependent variable: mathematics

           Independent variable   Coefficient   Standard error   Significance 
                       Constant         646.6              4.0 
             Traditional school          -3.9              2.5           .116 
                       Mobility         -15.5              2.1           .000 
               African American         -12.1              5.2           .019 
                         Latino         -12.8              3.7           .001 
                 Other minority          -1.1              5.2           .831 

N = 882

  F = 9.931 significance .000 Independent variable Coefficient Standard error
                                  Significance

Constant 637.6 4.0

                        Traditional school 0.8 2.5 .765

                  Mobility                     -12.7    2.1           .000 
              African American                 -13.8    5.3           .010 
                   Latino                       -4.8    3.7           .195 
               Other minority                    4.6    5.3           .388 
         Source: GAO data analysis.                             

Note: Special education and limited English proficiency were removed as
independent variables because the data received were considered
unreliable.

Appendix II: Tables of Regression Results for Differences in Student
Achievement Scores on State Assessments

Table 11: Regression Results for Differences in Student Performance on
State Reading Assessment at the Privately Managed and Comparison Schools
in Detroit

                      Detroit - Privately Managed School A

N = 208

  F = 6.428 significance .000 Independent variable Coefficient Standard error
               Significance Detroit - Privately Managed School B

                            Constant         309.8     7.3      
                  Traditional school          11.6     3.2              .000a 
                    African American         -16.2     6.9               .020 
                      Other minority         -10.0     10.2              .327 

N = 176

  F = 1.361 significance .257 Independent variable Coefficient Standard error
               Significance Detroit - Privately Managed School C

                           Constant         294.6     12.3     
                 Traditional school          -9.0     4.6             .054a,b 
                   African American           7.1     12.0               .556 
                     Other minority          12.9     26.5               .627 

N = 339
F = 19.182 significance .000
Independent variable Coefficient Standard error Significance

Constant 306.3 1.9
Traditional school -10.1 2.3 .000a
Detroit - Privately Managed School D
N = 418
F = 4.263 significance .000
Independent variable Coefficient Standard error Significance

Constant 285.2 14.7
Traditional school 6.8 2.1 .001a
African American 6.3 14.6 .666
Other minority 32.0 25.2 .205

Appendix II: Tables of Regression Results for Differences in Student
Achievement Scores on State Assessments

Detroit - Privately Managed School E

N = 186

  F = 3.450 significance .018 Independent variable Coefficient Standard error
               Significance Detroit - Privately Managed School F

                            Constant         300.8     16.9     
                  Traditional school           9.2     2.9              .002a 
                    African American          -3.5     16.7              .836 
                      Other minority          -7.1     19.3              .712 

N = 300

  F = 6.536 significance .002 Independent variable Coefficient Standard error
                                  Significance

Constant 286.8 2.4

                        Traditional school 9.3 2.8 .001a

                         Other minority -23.3 21.4 .276

                      Detroit - Privately Managed School G

N = 229

                          F = 5.014 significance .002

Independent variable Coefficient Standard error Significance

Constant 273.0 14.2
Traditional school 12.4 3.3 .000a
African American 11.9 14.2 .405
Other minority 18.8 16.7 .262

Detroit - Privately Managed School H
N = 367
F = 12.531 significance .000
Independent variable Coefficient Standard error Significance

Constant 283.8 3.0
Traditional school 12.4 2.4 .000
African American -5.2 4.2 .214
Other minority 7.9 6.7 .235
Latino -0.3 2.6 .893
Limited English proficiency -25.6 4.2 .000

Source: GAO data analysis.

Note: Where results do not include race or ethnic variables, all students
at the privately managed school and comparable schools used in the
regression analysis were African American.

Appendix II: Tables of Regression Results for Differences in Student
Achievement Scores on State Assessments

aUsing robust standard error procedures with clustering, the effect of
school type is not significant at the 95-percent confidence level.

bUsing robust estimation procedures without clustering, the effect of
school type is significant at the 95-percent confidence level.

Appendix II: Tables of Regression Results for Differences in Student
Achievement Scores on State Assessments

Table 12: Regression Results for Differences in Student Performance on
State Math Assessment at the Privately Managed and Comparison Schools in
Detroit

                      Detroit - Privately Managed School A

N = 208

  F = 8.573 significance .000 Independent variable Coefficient Standard error
               Significance Detroit - Privately Managed School B

                              Constant         529.4    12.2     
                    Traditional school          25.7     5.4            .000a 
                      African American         -15.2    11.5             .188 
                        Other minority          -6.0    16.9             .721 

N = 176

  F = 2.967 significance .0-34 Independent variable Coefficient Standard error
               Significance Detroit - Privately Managed School C

                              Constant         522.0    17.0     
                    Traditional school         -18.6     6.4            .004a 
                      African American           9.9    16.5             .549 
                        Other minority          23.7    36.5             .518 

N = 342
F = 13.258 significance .000
Independent variable Coefficient Standard error Significance

Constant 524.5 3.0
Traditional school 13.6 3.7 .000a
Detroit - Privately Managed School D
N = 420
F = 22.959 significance .000
Independent variable Coefficient Standard error Significance

                Constant                  512.0     20.2     
           Traditional school              23.5     2.8             .000 
            African American               -3.1     20.0            .876 
             Other minority                -0.5     34.6            .988 

Appendix II: Tables of Regression Results for Differences in Student
Achievement Scores on State Assessments

                      Detroit - Privately Managed School E

N = 188

  F = 2.977 significance .033 Independent variable Coefficient Standard error
               Significance Detroit - Privately Managed School F

                              Constant         572.1    28.7     
                    Traditional school          10.9     4.9            .028a 
                      African American         -54.4    28.3             .056 
                        Other minority         -58.5    34.6             .092 

N = 297

  F = 41.445 significance .000 Independent variable Coefficient Standard error
                                  Significance

Constant 500.2 3.7

                        Traditional school 37.9 4.2 .000

                         Other minority -16.2 31.3 .606

                      Detroit - Privately Managed School G

N = 231

                          F = 4.644 significance .004

Independent variable Coefficient Standard error Significance

Constant 505.7 20.4
Traditional school 17.7 4.8 .000
African American 7.0 20.4 .731
Other minority 15.7 24.0 .515

Detroit - Privately Managed School H
N = 366
F = 19.86 significance .000
Independent variable Coefficient Standard error Significance

Constant 498.8 4.1
Traditional school 27.0 3.3 .000
African American -5.1 5.7 .368
Other minority 12.7 9.0 .160
Latino 0.3 3.5 .934
Limited English proficiency -33.2 5.6 .000

Source: GAO data analysis.

Note: Where results do not include race or ethnic variables, all students
at the privately managed school and comparable schools used in the
regression analysis were African American.

Appendix II: Tables of Regression Results for Differences in Student
Achievement Scores on State Assessments

aUsing robust standard error procedures with clustering, the effect of
school type is not significant at the 95-percent confidence level.

Appendix III: Characteristics of Privately Managed Schools and Comparable
Traditional Public Schools in Detroit

           Privately Managed/             Percent free    Percent     Percent 
                  traditional  Enrollment and reduced   special ed   minority 
                  Private - A         867            68           3 
              Traditional - A         693            81           4 
              Traditional - B         538            58           3 
              Traditional - C         594            78           5 
                  Private - B         354            79          11 
              Traditional - A         594            78           5 
              Traditional - B         158            79           7 
              Traditional - C         389            74           3 
                  Private - C         322            39           8 
              Traditional - A         485            43          12 
              Traditional - B         434            47           4 
              Traditional - C         446            65           5 
                  Private - D        1108            46           3 
              Traditional - A         538            58           3 
              Traditional - B         369            47           4 
              Traditional - C         677            53           2 
                  Private - E         368            70           9 

          Traditional - A         389         74         3              98 
          Traditional - B         487         67         5             100 
          Traditional - C         524         62         5             100 
            Private - F           319         75         7              95 
          Traditional - A         214         68         7              89 
          Traditional - B         389         74         3              98 
          Traditional - C         451         80         0              98 
            Private - G           716         37         3             100 
          Traditional - A         538         58         3             100 
          Traditional - B         677         53         2             100 
          Traditional - C         369         47         4             100 
            Private - H           452         46         10             79 
          Traditional - A         561         73         0              76 
          Traditional - B         705         65         2              72 

Traditional - C 586 84 2 76 Sources: GAO data analysis from Common Core of
Data school year 2000-01 unless otherwise noted. Special education data
were from school Web sites. Limited English proficiency data were not
available.

Appendix IV: GAO Contacts and Staff Acknowledgments

GAO Contacts 	Deborah Edwards (202) 512-5416 Patricia Elston (202)
512-3016

Acknowledgments 	In addition to those named above, Peter Minarik, Mark
Braza, Douglas M. Sloane, and Shana Wallace made key contributions to this
report. Deidre M. McGinty and Randolph D. Quezada also provided important
support.

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