> **Supporting Statement for Paperwork Reduction Act Submission to
> OMB:**
>
> **Part A**
>
> **Individuals with Disabilities Education Act (IDEA) 2004 National
> Assessment Implementation Study (NAIS)**
>
> June 25, 2008
>
> *Prepared for*
>
> Lauren Angelo
>
> Project Officer
>
> Institute of Education Sciences
>
> U.S. Department of Education
>
> 555 New Jersey Ave., NW
>
> Washington, D.C. 20208
>
> *Prepared by*
>
> Abt Associates Inc.

Contents

[Part A Submission 1](#__RefHeading___Toc202088877)

[Introduction and Overview of the Study 1](#__RefHeading___Toc202088878)

[A1. Circumstances Requiring the Collection of Data
3](#__RefHeading___Toc202088879)

[A2. Purposes and Uses of the Data 3](#__RefHeading___Toc202088880)

[A3. Use of Information Technology to Reduce Burden
7](#__RefHeading___Toc202088881)

[A4. Efforts to Avoid Duplication 7](#__RefHeading___Toc202088882)

[A5. Economic Impact on Small Businesses or Entities
8](#__RefHeading___Toc202088883)

[A6. Consequences of Not Collecting the Information
8](#__RefHeading___Toc202088884)

[A7. Special Circumstances 8](#__RefHeading___Toc202088885)

[A8. Consultation Outside the Department of Education
8](#__RefHeading___Toc202088886)

[A9. Payment or Gifts to Respondents 9](#__RefHeading___Toc202088887)

[A10. Assurances of Data Privacy 9](#__RefHeading___Toc202088888)

[A11. Questions of a Sensitive Nature 10](#__RefHeading___Toc202088889)

[A12. Estimate of Respondent Burden 10](#__RefHeading___Toc202088890)

[A13. Estimate oTf Total Capital and Start-up Costs and Maintenance
Costs to Respondents or Record-Keepers 11](#__RefHeading___Toc202088891)

[A14. Estimate of Costs to the Federal Government
11](#__RefHeading___Toc202088892)

[A15. Changes in Burden 11](#__RefHeading___Toc202088893)

[A16. Plans for Analysis, Tabulation, Publication, and Schedule
11](#__RefHeading___Toc202088894)

[A17. Approval To Not Display Expiration Date
21](#__RefHeading___Toc202088895)

[A18. Exceptions to the Certificate Statement
21](#__RefHeading___Toc202088896)

[References 22](#__RefHeading___Toc202088897)

##### Appendix A: Copy of Statute

**Appendix B: State Part C Coordinator Survey**

**Appendix C: State 619 Coordinator Survey**

**Appendix D: Start Part B Administrator Survey**

**Appendix E: District Part B Administrator Survey**

**Appendix F: Crosswalk of Research Questions and Survey Items**

**Appendix G: Mathematical Proof of Why the Potential for Bias Resulting
from Not Refreshing Our Sample to Include "Births" in 2004 is Small**

**Appendix H: Calculation of Minimum Detectable Effects for
District-Level Proportions Using the IDEA National Implementation Study
(IDEA NAIS) District Sample**

[]{.mark}

[]{.mark}

[]{#__RefHeading___Toc202088877 .anchor}Part A Submission

[]{#__RefHeading___Toc202088878 .anchor}Introduction and Overview of the
Study

This document presents the Supporting Statement for the Individuals with
Disabilities Education Act (IDEA) National Assessment Implementation
Study (NAIS). The IDEA NAIS will examine how states and school districts
have implemented the 2004 Amendments to IDEA (IDEA 2004). The foci are
four key interrelated areas: (1) identification of children for early
intervention and special education; (2) early intervention service
delivery systems and coordination with special education; (3) academic
standards and personnel qualifications; and (4) dispute resolution and
mediation.

We are requesting OMB approval for the data collection activities
associated with the IDEA NAIS at this time. The total data collection
consists of three state-level surveys and one district-level survey.
Data are to be collected from all states and from a nationally
representative sample of school districts. In addition, extant data will
be retrieved to examine state policies regarding identification and
eligibility of children with disabilities for special education, highly
qualified staff definitions, and general demographic information on
states and school districts. Part A describes the justification for
these data collection activities. Part B, submitted under separate
cover, describes the statistical methods for selecting the nationally
representative sample of school districts and describes the techniques
to be used for analyses of the collected data.

The provision of educational services to children with disabilities has
a relatively short history in the context of U.S. education. Enactment
of the Education of the Handicapped Children's Act (EHA), P.L. 94-142,
in 1975, guaranteed that eligible children and youth with disabilities
would have available to them a free and appropriate public education
(FAPE), a program designed to meet each child's unique educational needs
in the least restrictive environment, and protection of the rights of
children and their families through procedural safeguards. Part B of the
law provides funds to states to assist them in providing FAPE to both
pre-school aged children (3-5) and school aged children (6-21) with
disabilities who are in need of special education and related services.
To be eligible for funding under the Preschool Grants program (Part B*,*
Section 619) a state must make FAPE available to all children with
disabilities residing in the state, ages 3 through 5. Since P.L. 94-142
was first enacted, the U.S. Department of Education's (ED) *Annual
Report to Congress* has chronicled the status of the implementation of
this landmark legislation. From these annual progress reports as well as
some policy studies and Congressional testimony, Congress has
reauthorized EHA eight times since its enactment in 1975. Major
modifications made to EHA through these reauthorizations are described
below.

Amendments to EHA in 1986 established the Early Intervention Program for
Infants and Toddlers with Disabilities under Part H (now Part C). The
Part C program assists states in developing and implementing a
statewide, comprehensive, coordinated, multidisciplinary, interagency
system to make early intervention services available to all children
with disabilities from birth through age 2 and their families.

During the 1990 reauthorization of EHA, the legislation was renamed the
Individuals with Disabilities Education Act (IDEA). The 1997
reauthorization of IDEA shifted legislative attention toward improving
educational results for children and youths with disabilities while
maintaining the emphasis on equal access to an education.
Standards-based reforms provided the policy framework for this IDEA
reauthorization, thus ensuring that students with disabilities could
have access to the same challenging curriculum as other students and
participate in assessments as a way to mark their progress toward
improved results.

The 1997 amendments of IDEA also required a National Assessment "to
examine how well schools, local education agencies, states and other
recipients of assistance" were making progress toward a number of goals
for children with disabilities and their families, in nine areas: (1)
improving academic performance, (2) increasing participation in the
general curriculum (3) improving transitions from preschool to school
and from school to work; (4) increasing the placement of students with
disabilities in the least restrictive environment; (5) decreasing the
drop out rate; (6) increasing the use of effective strategies for
addressing behavioral problems; (7) improving coordination of services;
(8) reducing disputes; and (9) increasing parent involvement.

To complete the requested assessment, ED's Office of Special Education
Programs (OSEP) commissioned seven studies, three of which were
topic-specific studies and four of which were longitudinal child
outcomes-based studies. The topic-specific studies included: (1) a study
of the costs of special education, (2) a study of personnel needs in
special education and; (3) the Study of State and Local Implementation
and Impact of the Individuals with Disabilities Education Act (SLIIDEA),
a longitudinal study of the implementation of IDEA at the state, local
and school levels.

The four longitudinal child outcomes studies addressed different
populations of students with disabilities, including: (1) the needs of
infants and toddlers served under Part C of IDEA; (2) pre-school aged
children with disabilities served under Part B, Section 619; (3)
elementary- and middle-school aged students with disabilities served
under Part B; and (4) high school students and youth with disabilities
served under Part B.

The most current reauthorization of IDEA, which occurred in 2004, again
instructs the Department of Education to carry out a National Assessment
of the law to measure: (1) progress in the implementation of IDEA 2004;
and (2) the relative effectiveness of the law in achieving its purposes.
A primary goal of the National Assessment of IDEA 2004 is to determine
how IDEA is being implemented with a focus on the changes resulting from
these most recent Amendments and ultimately how the implementation of
state and local programs in response to IDEA 2004 are associated with
academic and developmental outcomes for children with disabilities.

The IDEA NAIS under which the proposed data collection will occur is one
of four studies being supported by ED as part of the National Assessment
of IDEA 2004.[^1] The implementation study supported by the data
collection will include all states and a nationally representative
sample of school districts. The study will use three state level surveys
to gather information on state policies and program implementation as it
relates to (1) infants and toddlers with disabilities served under Part
C of IDEA, (2) preschool children with disabilities served under Part B,
Section 619 of IDEA, and (3) school aged children and youth served under
Part B of IDEA. A fourth, district level survey will be used to gather
local implementation data on children and youth served under Part B of
IDEA.

The study will be conducted by Abt Associates Inc. and its
subcontractors Westat and the Windwalker Corporation, under a 30 month
contract with ED's Institute of Education Sciences (IES), National
Center for Education Evaluation.

[]{#__RefHeading___Toc202088879 .anchor}A1. Circumstances Requiring the
Collection of Data

Collection of information is needed for the IDEA National Assessment
Implementation Study (NAIS) to assess state and school district
implementation of IDEA 2004. As noted, above, the IDEA NAIS is one of a
number of studies being conducted for the mandated National Assessment
of Progress under IDEA 2004 (see Appendix A for statutory language). The
studies to be carried out as part of the National Assessment of IDEA
2004 will build on and extend the knowledge generated from the studies
completed as part of the 1997 National Assessment and will focus on
changes resulting from the 2004 Amendments for which no systematic
information has yet been collected.

These changes, which addressed primarily the Part B program, continued
to align IDEA requirements with reforms underway in general education.
Changes are reflected in new Individualized Education Program (IEP)
provisions, and establishment of criteria for determining highly
qualified special education teachers. Other major changes included new
dispute resolution procedures, new special education eligibility
determination procedures, and increased flexibility in use of funds to
address disproportionate representation of selected demographic groups
in special education.

The IDEA NAIS, a new implementation study, will gather information on
state and local progress in implementing the new provisions of IDEA 2004
and will provide a comprehensive, representative national picture of the
implementation of early intervention and special education policies and
practices at the state and district levels. This information will be
useful to Congress in considering the success of the IDEA 2004 changes
in meeting desired goals, will provide information for future
reauthorizations of the Act, and will be useful to ED, researchers and
practitioners concerned with implementing policies and practices that
will ultimately lead to improved outcomes for students with
disabilities.

[]{#__RefHeading___Toc202088880 .anchor}A2. Purposes and Uses of the
Data

The data collected for the IDEA NAIS will be used by the U. S.
Department of Education to report to Congress on the implementation of
the 2004 Amendments to IDEA by states and districts. Failure to collect
implementation data may result in the Department being unable to
adequately report to Congress on the status of implementation of the
2004 Amendments to IDEA. The information can also be used to provide
context for impact studies of the 2004 Amendments and to guide future
projects on the implementation and impact of IDEA. Additionally, if this
study was not completed ED and Congress would not have an accurate
understanding of local and state special education policy and practice.
The information from the implementation study will assist Congress in
the reauthorization of the IDEA, and to further improve early
intervention and special education services with the ultimate goal of
improving outcomes for children with disabilities.

The data proposed to be collected for the study are needed to address 12
primary research questions listed below within the four focal areas for
the study:

**I. Identification of Children for Early Intervention and Special
Education**

1.  How do rates of identification of children for early intervention or
    special education vary according to the different disability
    definitions used by states?

2.  How does each state determine, under IDEA 2004, significant
    disproportionalities by race and ethnicity in the identification of
    students for special education for the districts within the state,
    and to what extent have districts been so identified?

3.  Which early intervening and/or Response to Intervention (RtI)
    strategies do districts use at various grade levels prior to the
    identification of children for special education?

4.  How do rates of identification for special education vary according
    to the use of different early intervening or RtI strategies? How do
    rates of identification for special education vary according to
    whether districts are required to adopt Early Intervening Services
    because of significant disproportionalities?

**II. Early Intervention Service Delivery and Coordination**

5.  Across states, what are the different models of service delivery for
    the Part C program supported through IDEA, and of coordination among
    the various early intervention and special education services
    provided through Part C and Part B?

**III. Academic Standards and Personnel Qualifications**

6.  Do state or district policies explicitly reference state academic
    standards, and do these policies require that goals and objectives
    on IEPs reference those standards?

7.  What are states and districts doing in terms of certification,
    professional development, and compensation for special education
    teachers to promote compliance with the "highly qualified teacher"
    provisions of IDEA and No Child Left Behind?

8.  How do the efforts of states and districts to provide a sufficient
    number of qualified early intervention and special education
    personnel for children with disabilities vary with state definitions
    of "highly qualified teacher" under NCLB?

**IV. Dispute Resolution and Mediation**

9.  Over time, have there been changes in the incidence of disputes
    between early intervention personnel and parents/guardians on issues
    related to identification for early intervention?

10. How does the incidence of disputes between early intervention
    personnel and parents/guardians regarding identification for early
    intervention vary with the use of mediation by states and districts?

11. Over time, have there been changes in the incidence of disputes
    between special education personnel and parents/guardians on issues
    related to special education services?

12. How does the incidence of disputes between special education
    personnel and parents/guardians regarding special education services
    vary with the use of mediation by states and districts?

The IDEA NAIS is a descriptive study that is based primarily on four
surveys that will provide a comprehensive picture of the State and local
implementation of IDEA 2004 across the age ranges 0-21. Three
state-level surveys will be fielded to collect data from: (1) State
special education administrators responsible for programs providing
special education services to school aged children with disabilities
(6-21); (2) State 619 coordinators who oversee preschool programs for
children with disabilities aged 3-5, and; (3) State IDEA Part C
coordinators who are responsible for early intervention programs serving
infants and toddlers. A fourth survey will be fielded at the district
level to collect data from local special education administrators about
preschool and school-age programs for children with disabilities aged
3-21. While state-level surveys will provide information on policies,
guidelines, and supports/resources, the district surveys focus more on
the strategies and procedures used to implement state policies.

Study Design

To assess the implementation of the 2004 Amendments to IDEA, the study
plans to survey state administrators of IDEA Part C and Part B programs
(including both preschool and school age programs) and a nationally
representative sample of district Part B administrators. In addition,
extant data gathered from state websites and taken from pre-existing
databases will be utilized to eliminate duplicative efforts and enable
longitudinal comparisons.

Data Collection Plan

This forms clearance submission covers the new data collection
activities to take place in the IDEA NAIS: (1) a paper survey to be
completed by State Part C Coordinators; (2) a paper survey to be
completed by State 619 Coordinators; (3) a paper survey to be completed
by State Part B Administrators; and, (4) a web-based survey to be
completed by a nationally representative sample of local education
agency (LEA or district) Part B Administrators. These surveys will be
conducted once in the fall of 2008 between September 2008 and December
2008.

Surveys will be sent to three state-level administrators each of whom is
responsible for a particular age group of children and students
receiving services through IDEA. The State Part B Administrator survey
will be completed by the individual in the state who is responsible for,
and thus knowledgeable of, service to students between the ages of 6 and
21. The individual responsible for, and knowledgeable of, services to
children between the ages of 3 and 5 will complete the State 619
Coordinator Survey. The State Part C Coordinator survey will be
addressed by the individual in charge of services to children from birth
to age 3. This group of three surveys is referred to as the "state
surveys."

The district-level survey will be sent to the district Part B
administrator, typically the special education director, who is
responsible for services to children between the ages of 6 and 21 in the
district. This survey is referred to as the "district survey." Following
is a brief description of the state- and district-level surveys. Copies
of the surveys can be found in Appendices B--E.

**State Surveys**

As noted, each state survey will ask the respondent questions about the
particular IDEA funded program for which he/she is responsible.
Information on policies, procedures, strategies and supports will be
gathered for a variety of topics that are common to each of the state
surveys, including:

-   Identification, eligibility and referral;

-   Early intervening services and response to intervention;

-   Personnel standards, and recruitment and retention issues;

-   State academic and developmental standards and their use in IEPs and
    IFSPs;

-   Parent/family involvement; and,

-   Frequency of disputes and uses of mediation and other dispute
    resolution strategies.

The state survey for Part C coordinators also asks about coordination
with Part B preschool programs, program organization and structure, and
funding and finance issues.

**District Survey**

A web-based questionnaire will be used to administer the district Part B
administrator survey to a nationally representative sample of 1,200
district Part B administrators. The district survey will collect
information on a series of topics that parallel those for the state
surveys, including:

-   Identification, eligibility and referral;

-   Early intervening and response to intervention;

-   Personnel standards, and recruitment and retention issues;

-   State academic and developmental standards and their use in IEPs and
    IFSPs;

-   Parent/family involvement; and,

-   Frequency of disputes and uses of mediation and other dispute
    resolution strategies.

**Extant Data**

In addition to the survey collection for which form clearance is
requested, extant data will be used to make use of data already
available and enable longitudinal comparisons. Extant data retrieval
will be conducted between January 2008 and December 2008.

A *review of state websites* will be conducted to provide information on
State policies regarding: (1) disability and eligibility definitions for
early intervention and special education; and (2) highly qualified
teachers and other personnel providing early intervention and special
education services.

*Extant databases* will be used to provide information to address the
research areas. Publicly accessible databases including National Early
Childhood Technical Assistance Center (NECTAC) Notes, Child Count Files
from Ideadata.org, the Part B Annual Performance Review, and the
National Association of State Directors of Special Education (NASDSE)
Summary of Part B will be used to provide information on identification.
The Part C Update, NECTAC Summary, Center to Inform Personnel
Preparation Policy and Practice in Early Identification and Preschool
Education Data Report, and the Part B and C Annual Performance Reviews
will be used to provide information on service delivery and
coordination. Part B Annual Performance Reviews, National Center on
Education Outcomes (NCEO), Participation/Accommodation Data and AYP
data, and the Education Commission of the States Child Outcomes Summary
Form (2006), the Schools and Staffing Survey (SASS), and the Integrated
Education Data System (IPEDS) will be used to provide information on
academic standards and personnel qualifications. Additionally
information from the Department's ED*Facts* will be used to provide
contextual information. Along with public use and ED*Facts* data, data
from the Study of State and Local Implementation and Impact of the
Individuals with Disabilities Education Act (SLIIDEA) [^2] will be used
to explore if there have been any changes over time in the frequency,
reason for, or mechanisms used to resolve disputes. SLIIDEA was
completed as part of the National Assessment of the 1997 Amendments to
IDEA.

Appendix F contains a crosswalk that shows which survey items and extant
data sources will be utilized to address the 12 research questions
guiding the IDEA NAIS.

[]{#__RefHeading___Toc202088881 .anchor}A3. Use of Information
Technology to Reduce Burden

The data collection plan for the IDEA NAIS reflects sensitivity to
issues of efficiency, accuracy, and respondent burden. Where feasible,
information will be gathered from existing sources, such as state
education agency websites and data warehouses, including EDFacts. The
data collection plan utilizes both paper and web-based surveys for
primary data collection.

Web-based surveys are gaining in popularity as increasing numbers of
respondents have e-mail and/or internet access. Advantages associated
with web-based surveys include potential substantial cost saving as no
duplication or mailing costs are incurred. Advances in the development
and administration of web-based surveys enable complex skip patterns in
surveys to be invisible to respondents. Additional costs associated with
data entry are not incurred as the respondent enters data while
completing the survey leading to improved data quality as well. The
nature of data entry in web-based surveys also leads to decreased costs
associated with processing and increased data collection speed.
Disadvantages associated with web-based surveys include: possible
technical issues associated with the design of the survey or connection
to the internet, and the differential use and familiarity of computer
technology by different groups of people.

The IDEA NAIS study team has extensive experience with both paper and
web-based surveys. Both methods were selected for the IDEA NAIS (i.e.,
paper for the state surveys, web for the district survey) to be the most
efficient and appropriate for specific respondent groups. The use of
different survey methods is driven primarily by sample size. Each state
survey will be administered to 51 respondents. The district survey will
be administered to 1200 respondents. Additionally, the district survey
includes many more complex skip patterns than the state surveys. As
noted earlier, programming of the skip patterns into the web-based
survey will increase the chances of individuals responding to only those
questions which are pertinent to their district. Thus, a web-based
survey was selected as the method most likely to result in accurate
study data for the district survey. Programming costs associated with a
web-based approach did not seem warranted for the state surveys, which
have only 51 respondents each.

[]{#__RefHeading___Toc202088882 .anchor}A4. Efforts to Avoid Duplication

There are two areas where duplication could arise in this type of study.
First, the research questions may have been addressed in other studies.
Second, the study may collect data which is already available through
other sources. To address the first area of potential duplication of
effort, we reviewed previous and on-going studies of IDEA implementation
to determine if these studies could yield data sufficient for addressing
the research questions for the IDEA NAIS. While a number of studies have
examined similar issues as part of the 1997 National Assessment (e.g.,
the Pre-Elementary Education Longitudinal Study, the Study of Personnel
Needs in Special Education) none can provide data on implementation
issues reflecting IDEA 2004. Moreover, the 2004 Amendments to IDEA
changed service provision sufficiently to render many of the findings of
previous studies unrelated to current regulations. Additionally, the
2004 Amendments added new provisions that have not yet been studied.
Thus, we are certain that currently available data on IDEA
implementation is not sufficient to address the research questions.

We addressed the second potential area of duplication through careful
review of existing publicly accessible databases that provide national
estimates related to special education programs. This resulted in
identification of data elements which can be used in conjunction with
survey items to answer the research questions. For example, we will be
using data compiled by the Education Commission of the States to examine
state definitions of highly qualified personnel for special education
teachers. We will also use existing demographic data available from
databases maintained by the National Center for Education Statistics,
from the website [www.ideadata.org]{.underline} and from EDFacts, to
gather state and district background and contextual information.

[]{#__RefHeading___Toc202088883 .anchor}A5. Economic Impact on Small
Businesses or Entities

No small businesses will be impacted by this project. The primary
entities for this study are school districts and state agencies. Burden
is minimized for all respondents by requesting only the minimum
information required to achieve the study objectives. Study contractors
will carefully specify information needs; questions to districts and
states will be restricted to generally available information maintained
in district and state administrative records.

[]{#__RefHeading___Toc202088884 .anchor}A6. Consequences of Not
Collecting the Information

Failure to collect the information proposed in this request will result
in non-compliance with the 2004 IDEA as the study was mandated by
Congress in Section 664 of the law (see Appendix A). Furthermore, not
collecting the data will prevent the U. S. Department of Education from
assessing the progress of states and school districts in implementing
the 2004 Amendments to IDEA, reporting to Congress on this progress, and
making improvements to policies and services for children with
disabilities. Additionally, there would be a lack of comprehensive and
representative information on early intervention and special education
state policies and implementation available to researchers and
practitioners.

[]{#__RefHeading___Toc202088885 .anchor}A7. Special Circumstances

There are no special circumstances required for the collection of this
information.

[]{#__RefHeading___Toc202088886 .anchor}A8. Consultation Outside the
Department of Education

Public comments were received and ED responded. These comments and
responses are attached. A team of researchers and analysts at Abt
Associates and Westat, led by Dr. Fran O'Reilly, developed the survey
instruments and data collection procedures. In addition, the Abt team
utilized three consultants: Dr. Beth Rous (University of Kentucky), Dr.
Margaret McLaughlin (University of Maryland), and Ms. Sharon Walsh
(Walsh Taylor In.).

The study employs a technical work group (TWG), consisting of eight
recognized experts on special education services to children from birth
to three years (Part C services), children between three and five years
of age (Part B, Section 619 services), and children between six and 21
years of age (Part B services). The following individuals serve on the
TWG:

Ms. Diana Allen, Cascade Regional Services

Dr. Mary Brownell, University of Florida

Dr. Mary-Beth Bruder, University of Connecticut Health Center

Dr. Pia Durkin, Attleboro School District

Dr. Mary-Beth Fafard, Brown University

Dr. Douglas Fuchs, Vanderbilt University

Dr. Jane Rhyne, Charlotte-Mecklenburg Public Schools

Dr. Patricia Snyder, University of Florida

[]{#__RefHeading___Toc202088887 .anchor}A9. Payment or Gifts to
Respondents

No payment or gifts to respondents will be provided.

[]{#__RefHeading___Toc202088888 .anchor}A10. Assurances of Data Privacy

None of the information collected will be reported or published in a
manner that would identify individual respondents.

Abt Associates and its subcontractors follow the confidentiality and
data protection requirements of IES (The Education Sciences Reform Act
of 2002, Title I, Part E, Section 183), which requires that all
collection, maintenance, use and wide dissemination of data conform to
the requirements of the Privacy Act of 1974 (5 U.S.C. 552a), the Family
Educational Rights and Privacy Act of 1974 (20 U.S.C. 1232g), and the
Protection of Pupil Rights Amendment (20 U.S.C. 1232h). The
Institutional Review Boards at Abt Associates and at Westat,
respectively have certified all members of the study team having access
to the data as having received training in the importance of
confidentiality and data security.

Abt Associates and its subcontractors will protect the confidentiality
of all information collected for the study and will use it for research
purposes only. The privacy procedures adopted for this study for all
data collection, data processing, and analysis activities include the
following:

-   All study respondents will be assured that strict rules will be
    followed to protect their privacy. The report prepared for this
    study will summarize district findings across the sample and will
    not associate responses with a specific district or individual. We
    will not provide information that identifies districts, or
    individuals to anyone outside the study team, except as required by
    law. However, policies and resources/supports may be reported by
    state.

-   Paper surveys will be sent to respondents and returned to Abt
    Associates via Federal Express. Using Federal Express ensures both
    rapid transmission of the material and allows for the tracking of
    surveys should problems arise.

-   To ensure data security, all individuals hired by Abt Associates
    Inc. are required to adhere to strict standards and sign an oath of
    confidentiality as a condition of employment. Abt's subcontractors
    will be held to the same standards.

-   Hard-copy data collection forms will be delivered to a locked area
    for receipt and processing. Abt Associates and Westat maintain
    restricted access to all data preparation areas (i.e., receipt,
    coding, and data entry). All data files on multi-user systems will
    be under the control of a database manager, with access limited to
    project staff on a "need-to-know" basis only.

-   Individual identifying information will be maintained separately
    from completed data collection forms and from computerized data
    files used for analysis. No respondent identifiers will be contained
    in public use files made available from the study, and no data will
    be released in a form that identifies individual respondents,
    districts or states.

-   All study staff involved in data collection or analysis will go
    through security clearance as mandated by the Department of
    Education.

```{=html}
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-   Identifiable data will be kept for three years after the project end
    date and then destroyed. Written records will be shredded and
    electronic records will be purged.

    []{#__RefHeading___Toc202088889 .anchor}A11. Questions of a
    Sensitive Nature

None of the four surveys include any questions of a sensitive nature.

[]{#__RefHeading___Toc202088890 .anchor}A12. Estimate of Respondent
Burden

Exhibit 1 presents our estimates of response burden for the data
collection activities requested for approval in this submission: three
state surveys (Part B, Part C and 619) and one district survey (Part B).
Each data collection activity will be administered once. The time
required to complete the survey is based on cognitive interviews of the
instruments with approximately six retired or former respondents for
each survey.

Assuming all 1,353 respondents complete the survey, the total reporting
burden associated with this data collection is 2,553 burden hours (see
Exhibit 1). The study will be carried out over roughly two and a half
years (30 months), from September 2007 to March 2010, with an annual
burden of 1,021 hours for 541 respondents.

  -------------------------- ---------------- ----------- --------------- ----------- --
  **Exhibit 1: Respondent                                                             
  Burden Estimates**                                                                  

  **Informant/Instrument**   **Number of      **Mean Time **Total                     
                             Responses^a^**   per         Respondent Time             
                                              Response    (Hours)**                   
                                              (Hours)**                               

                                                                                      

  **State Part B                                                                      
  Coordinator**                                                                       

  Survey                     51               1           51                          

  **State Part C                                                                      
  Coordinator**                                                                       

  Survey                     51               1           51                          

  **State 619 Coordinator**                                                           

  Survey                     51               1           51                          

  **District Part B                                                                   
  Administrator**                                                                     

  Survey                     1200             2           2400                        

  **Total**                  **1353**                     **2553**                    

  **^a^** Total respondents                                                           
  equal 50 states plus                                                                
  District of Columbia for                                                            
  state surveys and a random                                                          
  sample of 1200 school                                                               
  districts for the                                                                   
  district-level survey.                                                              

                                                                                      
  -------------------------- ---------------- ----------- --------------- ----------- --

[]{#__RefHeading___Toc202088891 .anchor}A13. Estimate of Total Capital
and Start-up Costs and Maintenance Costs to Respondents or
Record-Keepers

There are no annualized capital/start-up or ongoing operation and
maintenance costs involved in collecting the information.

[]{#__RefHeading___Toc202088892 .anchor}A14. Estimate of Costs to the
Federal Government

The estimated cost to the federal government to carryout the IDEA NAIS
is \$2,271,022. As the study will be carried out over roughly two and a
half years (30 months), the annual cost of the data collection in the
Request for OMB Approval of Data Collection Instruments and the analysis
of these data is \$908,409.

[]{#__RefHeading___Toc202088893 .anchor}A15. Changes in Burden

There is a program change of 1,021 hours as this is a new collection.

[]{#__RefHeading___Toc202088894 .anchor}A16. Plans for Analysis,
Tabulation, Publication, and Schedule

Analysis and Tabulation

This section describes our approach to empirical analyses of data for
the IDEA NAIS. The types of data being collected through the surveys and
extant data as discussed earlier primarily will provide descriptive
information on the processes and strategies in place at the state and
district levels regarding the implementation of IDEA 2004 in the four
broad areas targeted for this study: (1) identification of children for
early intervention and special education; (2) Part C service delivery
systems and coordination with the Part B program; (3) academic standards
and personnel qualifications; and (4) dispute resolution and mediation.

[]{.mark}

Most of the research questions will be easily addressed through the use
of simple descriptive statistics such as means and percentages, as well
as cross-tabulations to illustrate the distribution of policies and
procedures across states and districts with varying characteristics. We
will also have the opportunity to examine several outcomes
(identification rates and incidence of disputes), and to contrast
outcomes across populations and time frames. For example, some of the
research questions require that we examine relationships between various
inputs (disability definitions, Early Intervening Services (or EIS)) and
variation in these outcomes. Our general approach to the analytic
methods we propose to use and the methodological issues associated with
the required analyses are described below. The discussion focuses on
methodological issues as they relate to:

-   type of inference (simple descriptive, change over time, differences
    among groups);

-   unit of analysis (state, district);

-   time frame covered by analysis (single time-point, longitudinal) ;
    and,

-   missing data (survey non-response, item non-response)

In the course of conducting the analyses to answer the research
questions, practically every combination of these four topics will come
into play for both the state and district level data. As will be evident
from examples, the analytic methods we describe below cut across all 12
research questions. We discuss in turn our approach to each type of
analysis.

Descriptive Analyses: Single Time Point

State-level Data

The State-level surveys (Part B, Part C and 619) will be administered to
all 50 states and the District of Columbia. No survey non-response is
anticipated for two reasons. First, our experience with collecting data
from State agency respondents demonstrates that it is reasonable to
expect there will be no survey non-response. In the SLIIDEA study, we
received 100 percent state response rates for all waves of data
collection (Schiller et al., 2006, p. 11). Westat has had similar
successful response rates in their data collection efforts (e. g.,
Markovitz et al., 2006, p. 15). Both Abt Associates and Westat staff
have long-standing working relationships with state administrators that
facilitate data collection efforts. Second, as IDEA is a Federal grant
program, states technically are required to participate in studies such
as this one in order to continue receiving funds (Education Department
General Administrative Regulations (Sec. 75.591, 20 U.S.C. 1221e-3 and
3474)). A letter from ED reminding respondents of this obligation will
also facilitate the expected high response rate. Therefore, we expect
the questionnaire responses will represent a census of the states.

State-level analyses will generally be presented in the form "the
percent of states that\...." Consider, for example, the survey item we
intend to include on the State Part B Administrator survey:

1.  **What best describes the status of your state's progress in
    defining significant disproportionality? Select one.**

+--------------------------------------------------------------+-------+
| a.  Our state's definition of significant disproportionality |       |
|     for 2008-09 is finalized and no changes are anticipated  |       |
+--------------------------------------------------------------+-------+
|                                                              |       |
+--------------------------------------------------------------+-------+
| b.  Our state's definition of significant disproportionality |       |
|     for 2008-09 is finalized but we are planning             |       |
|     modifications or revisions in the coming year            |       |
+--------------------------------------------------------------+-------+
|                                                              |       |
+--------------------------------------------------------------+-------+
| c.  Our state's definition of significant disproportionality |       |
|     for 2008-09 is in the process of being developed         |       |
+--------------------------------------------------------------+-------+

In the case of no missing data, the calculation of the percent of states
reporting that their state's definition of disproportionality for the
2008-09 school year is finalized with no changes anticipated (response
option a) is simply 100 multiplied by the number of states that selected
response option a, divided by 51. We represent this calculation
algebraically as:

$$\text{100} \ast \frac{\sum_{}^{}X}{\text{51}}$$

where *X* = 1 if the state's response is a and *X* = 0 if the state's
response is not a, and Σ~51 ~represents summation over the 51 responses
(50 states and the District of Columbia).

Since the data are a census, rather than a sample, there is no need for
calculation of standard errors or confidence intervals as these are
statistical concepts that apply to sample data. It is common to present
the standard error of an *estimate* or a 95% confidence interval around
an *estimate*, but in this case, the percent calculated is not an
estimate but is in fact the true population value. An illustrative table
for this type of state level analysis is shown in Exhibit 2.

+----------------------------------+---+---+---+---+--------+--------+
| **Exhibit 2: Percent and Number  |   |   |   |   |        |        |
| of States Reporting Status of    |   |   |   |   |        |        |
| Definition for Significant       |   |   |   |   |        |        |
| Disproportionality (2008-2009    |   |   |   |   |        |        |
| School Year)**                   |   |   |   |   |        |        |
+----------------------------------+---+---+---+---+--------+--------+
| **As of 2008 -- 09, our state's  | * |   | * |   | **Mis  | *      |
| definition of significant        | * |   | * |   | sing** | *Total |
| disproportionality is:**         | Y |   | N |   |        | ^a^**  |
|                                  | e |   | o |   |        |        |
|                                  | s |   | * |   |        |        |
|                                  | * |   | * |   |        |        |
|                                  | * |   |   |   |        |        |
+----------------------------------+---+---+---+---+--------+--------+
|                                  | * | * | * | * |        |        |
|                                  | * | * | * | * |        |        |
|                                  | N | % | N | % |        |        |
|                                  | * | * | * | * |        |        |
|                                  | * | * | * | * |        |        |
+----------------------------------+---+---+---+---+--------+--------+
| Finalized and no changes are     |   |   |   |   |        |        |
| anticipated                      |   |   |   |   |        |        |
+----------------------------------+---+---+---+---+--------+--------+
| Finalized but modifications or   |   |   |   |   |        |        |
| revisions are planned for the    |   |   |   |   |        |        |
| coming year                      |   |   |   |   |        |        |
+----------------------------------+---+---+---+---+--------+--------+
| In the process of being          |   |   |   |   |        |        |
| developed                        |   |   |   |   |        |        |
+----------------------------------+---+---+---+---+--------+--------+
| *Source:* State Part B           |   |   |   |   |        |        |
| Administrator Questionnaire --   |   |   |   |   |        |        |
| Item 1                           |   |   |   |   |        |        |
|                                  |   |   |   |   |        |        |
| ^a^ Total refers to the number   |   |   |   |   |        |        |
| of states that answered the      |   |   |   |   |        |        |
| question.                        |   |   |   |   |        |        |
+----------------------------------+---+---+---+---+--------+--------+

Although we do not anticipate survey non-response, we will treat item
non-response and survey non-response in the same manner. First, we will
indicate in our tables the number of missing responses (see Exhibit 2).
Additionally, we will decrease the denominator by the number of missing
responses. This means the summation represents the number of states
responding to the item.

District-level Data

Unlike state-level data where we have a census of respondents, we are
collecting data for a sample of school districts. That is, the District
Part B Administrator Survey will be administered to a nationally
representative sample of school districts that includes a planned
overlap sample with SLIIDEA to support longitudinal analyses. By
"overlapping samples" we mean that a proportion of districts in the IDEA
NAIS district sample were also in the 2004-2005 SLIIDEA sample, but
there will also be districts in each of the two study samples that are
not in the other. The analyses described above for states are not fully
applicable to the district level data because we will be using estimates
to represent all school districts in the nation; therefore, different
analytic techniques are required. As IDEA is a Federal grant program,
districts technically are required to participate in studies such as
this one in order to continue receiving funds (Education Department
General Administrative Regulations (Sec. 75.591, 20 U.S.C. 1221e-3 and
3474)).

In reporting our results for school districts, we will often make
statements that begin with, "the percent of districts that \...." We
will design our analyses such that the interpretation of "percent of
districts" corresponds to the percent of districts out of all school
districts in the country, not just the school districts that happen to
be in the sample. In order to calculate statistics that are nationally
representative, the sampling design must be taken into account. We
provide the calculation algorithm below. Note that if the survey item is
dichotomous (0/1), then the process described below to estimate a mean
actually results in the estimation of a proportion. Multiplying the
proportion by 100 will give a percentage.

Let:

> *y~hi~* be the response on a survey item for district *i* in stratum
> *h*,
>
> *w~hi~* = the sampling weights for district *i* in stratum *h*,
>
> $\overline{P}$ = the estimator of the population percentage,
>
> $\overline{Y}$ = the estimator of the population mean,
>
> $\hat{Y}$ = the estimator of the population total,
>
> $\hat{M}$ = the estimator of the number of elements (districts) in the
> population,
>
> *h* = 1, \..., *L* enumerate the strata (for the current design,
> L=12),
>
> *i* = 1, \..., *n~h~* , enumerate the sampled districts in stratum
> *h*, note that the
>
> districts are the primary sampling units (PSUs), and *n~h\ ~*is the
> number
>
> of sampled districts in stratum *h*.

Then:

$\hat{Y} = \sum_{h = 1}^{L}{\sum_{i = 1}^{n_{h}}{w_{\text{hi}}y_{\text{hi}}}}$,

$\hat{M} = \sum_{h = 1}^{L}{\sum_{i = 1}^{n_{h}}w_{\text{hi}}}$,

$\overline{Y} = \hat{Y}/\hat{M}$,

$$\overline{P} = \text{100} \ast \overline{Y}$$

The estimator given above for $\overline{Y}$ is known as a *combined*
ratio estimator. We note that the sum of the sample weights,$\hat{M}$,
is an estimate of the number of school districts in the population. When
we know the true population value of *M*, as we do in the current
example where we know the number of districts in each stratum, we also
have the option of using a *separate* ratio estimator. The separate
ratio estimator is defined as:

${\overline{Y}}_{s} = \frac{\sum_{h = 1}^{L}{M_{h}\frac{{\hat{Y}}_{h}}{{\hat{M}}_{h}}}}{M}$

where, $M = \sum_{h = 1}^{L}M_{h}$is the sum of the known school
district sizes and L is the number of strata.

The separate ratio estimator estimates the ratio within each stratum and
then forms a weighted average of these separate estimates into a single
estimate of the population ratio while the combined ratio estimator is a
ratio estimate pooled over all strata.  In cases were there is a lot of
variation among strata means, the separate ratio estimator is frequently
chosen as it takes advantage of the extra efficiency provided by the
stratification and provides a more precise estimate. Determination of
whether we will use the combined ratio estimator or the separate ratio
estimator will be made based on the amount of variation among strata
means. If the stratum by stratum ratio estimates are nearly equal we
will use the combined ratio estimator. If they are very different we
will use the separate ratio estimator.

The expected precision of the estimates with a sample of 1200 LEAs and
an expected 80 percent response rate (previously achieved in Schiller et
al., 2006, p. 11) would be plus or minus 3.9 percentage points assuming
a design effect of 1.6 because of the unequal sampling weights. As IDEA
is a Federal grant program, districts are technically required to
participate in studies such as this one in order to continue receiving
funds (as are states). A letter from ED reminding respondents of this
obligation will also facilitate the expected high response rate.

***Statistical Software for Calculating Parameter Estimates and Standard
Errors.*** The estimator of the population mean, shown above, can be
easily calculated in statistical software packages that are designed for
analysis of complex survey data including the estimation of mean and
variance. We can use the variance estimates to produce standard errors
and 95% confidence intervals around the estimates of the population
means for the district level data.

Exhibit 3 provides an example of this type of analysis at the district
level.

+------------------------+------+------+------+------+--------+--------+
| **Exhibit 3: Percent   |      |      |      |      |        |        |
| of Districts That Are  |      |      |      |      |        |        |
| Required to Provide    |      |      |      |      |        |        |
| EIS Due to Significant |      |      |      |      |        |        |
| Disproportionality     |      |      |      |      |        |        |
| (2008-2009 School      |      |      |      |      |        |        |
| Year)**                |      |      |      |      |        |        |
+------------------------+------+------+------+------+--------+--------+
|                        | **Y  |      | **   |      | **Mis  | **Tota |
|                        | es** |      | No** |      | sing** | l^a^** |
+------------------------+------+------+------+------+--------+--------+
|                        | \%   | (SE) | \%   | (SE) | N      | N      |
+------------------------+------+------+------+------+--------+--------+
| Required to provide    |      |      |      |      |        |        |
| EIS                    |      |      |      |      |        |        |
+------------------------+------+------+------+------+--------+--------+
| *Source:* District     |      |      |      |      |        |        |
| Part B Questionnaire - |      |      |      |      |        |        |
| Item 1                 |      |      |      |      |        |        |
|                        |      |      |      |      |        |        |
| ^a^ Total refers to    |      |      |      |      |        |        |
| the number of          |      |      |      |      |        |        |
| districts that         |      |      |      |      |        |        |
| answered the question. |      |      |      |      |        |        |
|                        |      |      |      |      |        |        |
| Note: Percentages and  |      |      |      |      |        |        |
| standard errors are    |      |      |      |      |        |        |
| population estimates   |      |      |      |      |        |        |
| calculated from        |      |      |      |      |        |        |
| weighted data. The     |      |      |      |      |        |        |
| numbers shown for      |      |      |      |      |        |        |
| missing and total Ns   |      |      |      |      |        |        |
| were calculated from   |      |      |      |      |        |        |
| unweighted data.       |      |      |      |      |        |        |
+------------------------+------+------+------+------+--------+--------+

Descriptive Analyses: Change Over Time Analyses

By "change over time analyses," we mean simple descriptions of change in
a variable over time. This is distinct from a model where we try to
assess the relationship between some predictor variable(s) and the
change in the outcome variable over time. For the IDEA NAIS, we will be
able to examine change over time at both the state and district levels
where we have repeated items from SLIIDEA.

State-level Data

State-level change over time analyses will utilize extant SLIIDEA data,
and data from a new survey of state Part B administrators. Since the
state data at each time point represent a census rather than a sample of
states, the summary tables will not include standard errors, confidence
intervals or p-values. Any differences observed between time points will
represent a difference in the true mean. There will be no sampling
uncertainty associated with any of the numbers in the table. Exhibit 4
provides an example of this type of analysis at the state level.

<table style="width:100%;">
<colgroup>
<col style="width: 11%" />
<col style="width: 7%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 6%" />
<col style="width: 7%" />
<col style="width: 10%" />
</colgroup>
<tbody>
<tr class="odd">
<td colspan="14"><strong>Exhibit 4: State Completed Formal Mediations
During the Last School Year</strong></td>
</tr>
<tr class="even">
<td rowspan="2"></td>
<td colspan="3"><strong>2002-2003 School Year<br />
(SLIIDEA)</strong></td>
<td colspan="3"><strong>2003-2004 School Year<br />
(SLIIDEA)</strong></td>
<td colspan="3"><strong>2004-2005 School Year<br />
(SLIIDEA)</strong></td>
<td colspan="3"><strong>2007-2008 School Year<br />
(IDEA NAIS)</strong></td>
<td><strong>Difference (2007-2008 – 2004-2005)</strong></td>
</tr>
<tr class="odd">
<td><strong>Yes %</strong></td>
<td><strong>Yes N</strong></td>
<td><strong>Total N</strong></td>
<td><strong>Yes %</strong></td>
<td><strong>Yes N</strong></td>
<td><strong>Total N</strong></td>
<td><strong>Yes %</strong></td>
<td><strong>Yes N<sup>a</sup></strong></td>
<td><strong>Total N</strong></td>
<td><strong>Yes %</strong></td>
<td><strong>Yes N</strong></td>
<td><strong>Total N</strong></td>
<td><strong>Percentage Points</strong></td>
</tr>
<tr class="even">
<td>Formal mediations</td>
<td>100.0</td>
<td>50</td>
<td>50</td>
<td>98.0</td>
<td>49</td>
<td>50</td>
<td>96.0</td>
<td>48</td>
<td>50</td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr class="odd">
<td colspan="14"><p><sup>a</sup> N includes one state that did not
provide us number of formal mediations completed, but where follow-up
questions implied at least one such mediation was completed.</p>
<p><em>Sources:</em> SLIIDEA Wave 2 State Questionnaire – Item 16 ;
SLIIDEA Wave 3 State Questionnaire – Item 18; SLIIDEA Wave 4 State
Questionnaire – Item 17; IDEA NAIS State Part B –Item 42</p></td>
</tr>
</tbody>
</table>

District-level Data

District-level change over time analyses will utilize extant SLIIDEA
data and new data from the IDEA NAIS of a nationally representative
sample of 1200 districts. An example of a change over time analysis at
the district level is given in Exhibit 5. It shows the percent of
districts that conducted or participated in various types of dispute
resolution procedures as estimated from three separate school years.
Data from the first two years (columns labeled 2002-2003 and 2004-2005,
respectively) will come from the extant SLIIDEA data set and will be
transcribed from previous SLIIDEA reports. Data for the third year
(column labeled 2007-2008) will be obtained from administration of the
IDEA NAIS survey of district Part B administrators to the nationally
representative sample of 1200 districts and will be calculated as
described earlier. Examination of this table will provide descriptive
data on whether the percentages of districts that conducted or
participated in various dispute resolution procedures fluctuated over
time. The example table shows means and standard errors. The final
column of the table will show the difference between the means for the
2007-2008 school year and the 2004-2005 school year and the standard
error of the difference. A mean difference that is greater in absolute
value than two times the standard error of the difference is a
statistically significant difference at the .05 level.

+--------------------------------+--------+--------+--------+--------+
| **Exhibit 5: District          |        |        |        |        |
| Conducted or Participated in   |        |        |        |        |
| Dispute Resolution             |        |        |        |        |
| Procedures**                   |        |        |        |        |
+--------------------------------+--------+--------+--------+--------+
|                                | **%    |        |        |        |
|                                | (SE)   |        |        |        |
|                                | of     |        |        |        |
|                                | Dis    |        |        |        |
|                                | tricts |        |        |        |
|                                | that   |        |        |        |
|                                | partic |        |        |        |
|                                | ipated |        |        |        |
|                                | in     |        |        |        |
|                                | proced |        |        |        |
|                                | ures** |        |        |        |
+--------------------------------+--------+--------+--------+--------+
| **Type of Procedure**          | **200  | **\    | **\    | *      |
|                                | 2-2003 | 200    | 200    | *Diffe |
|                                | School | 4-2005 | 7-2008 | rence\ |
|                                | Year** | School | School | (200   |
|                                |        | Year** | Year** | 7-2008 |
|                                | *      |        |        | --     |
|                                | *(SLII | *      | *      | 2004-2 |
|                                | DEA)** | *(SLII | *(IDEA | 005)** |
|                                |        | DEA)** | N      |        |
|                                |        |        | AIS)** |        |
+--------------------------------+--------+--------+--------+--------+
| Informal dispute resolution    | 25.4   | 25.6   |        |        |
| procedure                      | (2.4)  | (2.3)  |        |        |
+--------------------------------+--------+--------+--------+--------+
| Mediation following a due      | 11.9   | 12.3   |        |        |
| process request                | (1.5)  | (1.5)  |        |        |
+--------------------------------+--------+--------+--------+--------+
| Impartial due process hearing  | 10.5   | 10.4   |        |        |
|                                | (1.3)  | (1.3)  |        |        |
+--------------------------------+--------+--------+--------+--------+
| State administrative review of | 3.7    | 3.2    |        |        |
| hearing decision               | (1.2)  | (0.9)  |        |        |
+--------------------------------+--------+--------+--------+--------+
| State/Federal court review of  | 1.8    | 1.3    |        |        |
| hearing decision               | (0.5)  | (0.3)  |        |        |
+--------------------------------+--------+--------+--------+--------+
| Litigation                     | 3.3    | 3.6    |        |        |
|                                | (0.7)  | (0.7)  |        |        |
+--------------------------------+--------+--------+--------+--------+
| *Sources:* SLIIDEA Wave 1      |        |        |        |        |
| District Questionnaire --      |        |        |        |        |
| Items K1a-K1d, K2; SLIIDEA     |        |        |        |        |
| Wave 2 District Questionnaire  |        |        |        |        |
| -- Items 25, 26a-26f ; SLIIDEA |        |        |        |        |
| Wave 4 District Questionnaire  |        |        |        |        |
| -- Items 27, 28a-28f; IDEA     |        |        |        |        |
| NAIS District Part B -- Items  |        |        |        |        |
| 61, 62a-62g                    |        |        |        |        |
+--------------------------------+--------+--------+--------+--------+

The analytically challenging task for this type of analysis is the
calculation of the standard error of the difference (i.e., the last
column in Exhibit 5). The challenges arise from the need to take into
account that the data from the 2008-2009 IDEA NAIS survey and the
2004-2005 SLIIDEA surveys are comprised of overlapping samples, and that
the estimates at each time are derived from different samples having
different sampling weights and potentially different design effects. The
method proposed below for calculating the standard error of the
difference in overlapping samples was adapted from the method described
by Kish (1965).

We are interested in estimating the difference between two population
proportions from two points in time. In addition to reporting the
estimate, the precision of the estimate needs to be reported by
computing the standard error of the estimated difference. The simple
case has two independent samples at the two time points, thus, the
variance of the difference between the two sample proportions is simply
the sum of the variance of the first proportion and the variance of the
second proportion.

The IDEA NAIS study, however, is not an example of the simple case.
Rather, there is a planned overlap of some school districts between the
two samples.  Therefore, the variance of the difference is no longer a
sum of the variances; rather, it also includes a covariance. The
variance of the difference is smaller than if there were two independent
samples. The degree to which the variance in the estimate for the
overlapping samples is reduced depends on the amount of overlap and the
correlation coefficient between the estimates at two time periods. Kish
(1965) provides a formula that computes the variance of the difference
taking into account the amount of overlap and the correlation between
two time periods as described below.

Let $p_{1}$ denote the estimated proportion from the 2007-2008 sample,
with sample of size $n_{1}$. Let $p_{2}$ denote the proportion from the
2004-2005 sample, with sample of size $n_{2}$. Let $m$ denote the amount
of overlap between the two samples. We are interested in obtaining the
standard error of the difference between the two sample proportions. We
can write the estimated variance of the difference between the two
sample proportions as:

$$v(p_{1} - p_{2}) = v(p_{1}) + v(p_{2}) - 2m\text{cov}(p_{1},p_{2})$$

where,$v(p_{1})$is the estimated variance of the 2008-2009 proportion
based on a sample of $n_{1}$ units and $v(p_{2})$is the estimated
variance of the 2004-2005 proportion based on $n_{2}$ units.

Under simple random sampling, the estimated variance of the difference
in two sample proportions becomes

$$v(p_{1} - p_{2}) = \frac{p_{1}(1 - p_{1})}{n_{1}} + \frac{p_{2}(1 - p_{2})}{n_{2}} - 2m\frac{p_{\text{12}} - p_{1}p_{2}}{n_{1}n_{2}}$$

where $p_{\text{12}}$ is the proportion having the attribute in both the
samples based on a sample of $m$ units. The district-level data from the
two samples must be merged to calculate the quantity $p_{\text{12}}$.

For estimating the variance under the complex design used in SLIIDEA and
proposed for the current study, we can first estimate the variance under
simple random sampling using the formula given above but with weighted
proportions. Then, we multiply the variance by the design effect, or the
average of the design effects from the two studies.

To implement this method we will obtain the variances under the complex
design for the two samples using SUDAAN as the values for $v(p_{1})$ and
$v(p_{2})$, and estimate the covariance as
$\text{cov}(p_{1},p_{2}) = \rho_{p_{1}p_{2}}\sqrt{v(p_{1})v(p_{2}})$,
where the correlation term $\rho_{p_{1}p_{2}}$ is calculated as the
correlation between 2008-2009 and 2004-2005 measurements for the
districts that were measured at both time points. Merging of
district-level data is required to calculate this quantity.

The square root of the variance gives the standard error of the
difference in the two proportions recognizing that we have overlapping
samples and thus that the samples are not independent. The standard
error can be reported in a table as shown above in Exhibit 5, or can be
used to create 95% confidence intervals for the difference, or used in a
statistical test of the null hypothesis of equivalent proportions in the
two groups.

A Design Limitation for Longitudinal Analyses

The comparison of results from the IDEA NAIS survey to the results from
the 2004-2005 SLIIDEA survey would ideally represent the differences
between the national populations at those two time points. However, a
limitation of the current design arises from the fact that the SLIIDEA
sample of districts was selected to be representative of the national
population of school districts in school year 1997-1998. Those districts
were followed over time, with the final wave of data collection
occurring during the 2004-2005 school year. Since the SLIIDEA sample was
not refreshed each year to reflect any new districts that came into
existence after 1997, it may be a biased estimator of the national
population of districts in 2004-2005. It would not be a biased estimator
if the causal mechanism of new births of districts that occurred between
1997 and 2004 were completely uncorrelated with the outcomes measured.
We cannot know that correlation. However, we do know that the potential
for bias is small because less than 2% of the districts that existed in
2004 did not exist in 1997.

The estimate we have in the SLIIDEA study is basically an estimate of
what the 1997 districts were doing in 2004 because we did not update our
sample to include \"new births.\" The number of new births (2%) is so
small that even if we had included them all they would not change our
estimate by very much (see Appendix G for the proof supporting this
claim).

Analyses of Differences Among Groups

The main purpose of the study is to describe state and district polices
and practices related to early intervention and special education
services. However, not all states or districts are similar in how they
choose to implement early intervention and special education services to
children with disabilities. Thus, the study will also examine
differences among groups on selected policies and practices.

State-level Data

The twelfth research question of the study which asks "How does the
incidence of disputes between special education personnel and
parents/guardians regarding special education services vary with the use
of mediation by states?" The response to this question will require
classification of states into groups defined on the basis of how often
they use mediation, and comparison of dispute rates between those
groups. The comparisons would likely involve showing the mean, median,
minimum, and maximum. As discussed in previously described analytic
approaches, since the state data represent a census rather than a sample
of states, the summary tables will not include standard errors,
confidence intervals or p-values. Any differences observed between
groups represent true differences. There will be no sampling uncertainty
associated with the state data. An illustrative example is provided in
Exhibit 6.

+--------------------------+------+----------+---------+------+------+
| **Exhibit 6: Rate of     |      |          |         |      |      |
| Impartial Due Process    |      |          |         |      |      |
| Hearings Completed by    |      |          |         |      |      |
| Number of Formal         |      |          |         |      |      |
| Mediations completed by  |      |          |         |      |      |
| States**                 |      |          |         |      |      |
+--------------------------+------+----------+---------+------+------+
|                          |      | **Rate   |         |      |      |
|                          |      | of       |         |      |      |
|                          |      | I        |         |      |      |
|                          |      | mpartial |         |      |      |
|                          |      | Due      |         |      |      |
|                          |      | Process  |         |      |      |
|                          |      | He       |         |      |      |
|                          |      | arings** |         |      |      |
+--------------------------+------+----------+---------+------+------+
|                          |      |          |         | *    |      |
|                          |      |          |         | *Ran |      |
|                          |      |          |         | ge** |      |
+--------------------------+------+----------+---------+------+------+
| **Number of Formal       | *    | **Mean** | **M     | **L  | **Hi |
| Mediations^a^**          | *N** |          | edian** | ow** | gh** |
+--------------------------+------+----------+---------+------+------+
| 0                        |      |          |         |      |      |
+--------------------------+------+----------+---------+------+------+
| 1-20                     |      |          |         |      |      |
+--------------------------+------+----------+---------+------+------+
| 20-50                    |      |          |         |      |      |
+--------------------------+------+----------+---------+------+------+
| 50+                      |      |          |         |      |      |
+--------------------------+------+----------+---------+------+------+
| a Categories will be     |      |          |         |      |      |
| created based on the     |      |          |         |      |      |
| distribution of          |      |          |         |      |      |
| responses to this item   |      |          |         |      |      |
| and may include number   |      |          |         |      |      |
| of mediations per 10,000 |      |          |         |      |      |
| students with            |      |          |         |      |      |
| disabilities.            |      |          |         |      |      |
|                          |      |          |         |      |      |
| *Source:* IDEA NAIS      |      |          |         |      |      |
| Extant State Policy Data |      |          |         |      |      |
| and Part B Survey --     |      |          |         |      |      |
| Item 42, 47, 48,         |      |          |         |      |      |
+--------------------------+------+----------+---------+------+------+

District-level Data

We also anticipate comparing outcomes among groups of districts in the
nationally representative district sample. An example of a research
question requiring this type of analysis is research question 4a. It
asks, "How do the rates of identification for special education vary
according to use of different early intervening strategies?" This
analysis will involve the classification of districts into mutually
exclusive and exhaustive categories based on distribution of early
intervening service (EIS) activities and resources. Summary tables will
show the mean and standard error (or 95% confidence intervals) of
identification rates for each classification group of districts (e.g.,
mandatory; voluntary) (see Exhibit 7 for an example of such a table).
Other statistics such as the minimum, maximum, and median for each group
may also be deemed as informative and included in the tables.

  ------------------------ ------- ---------------- ------------ ----------- ---------- -------------
  **Exhibit 7: Rate of                                                                  
  Identification for                                                                    
  Special Education                                                                     
  Students by Distribution                                                              
  of Early Intervening                                                                  
  Services Activities or                                                                
  Resources**                                                                           

                                   **Rate of                                            
                                   Identification                                       
                                   of Special                                           
                                   Education                                            
                                   Students**                                           

                                                                 **Range**              **P-value**

  Early Intervening        **N**   **Mean (SE)**    **Median**   **Low**     **High**   
  Services Activities                                                                   

  Early Intervening                                                                     
  Services activities or                                                                
  resources are not                                                                     
  distributed to                                                                        
  individual schools                                                                    

  Early Intervening                                                                     
  Services activities or                                                                
  resources are                                                                         
  distributed only to                                                                   
  schools with evidence of                                                              
  significant                                                                           
  disproportionality                                                                    

  Early Intervening                                                                     
  Services activities or                                                                
  resources are                                                                         
  distributed to all                                                                    
  schools, regardless of                                                                
  whether they show                                                                     
  significant                                                                           
  disproportionality                                                                    

  *Source:* IDEA NAIS                                                                   
  District Part B -- Item                                                               
  3                                                                                     
  ------------------------ ------- ---------------- ------------ ----------- ---------- -------------

Publication and Study Schedule

The schedule for key study activities and published reports is presented
below.

+--------------------------------------+---+-------------------------------+
| > **Study Schedule**                 |   |                               |
+--------------------------------------+---+-------------------------------+
| > **Key Activity or Report**         | > |                               |
|                                      |   |                               |
|                                      | * |                               |
|                                      | * |                               |
|                                      | T |                               |
|                                      | i |                               |
|                                      | m |                               |
|                                      | i |                               |
|                                      | n |                               |
|                                      | g |                               |
|                                      | * |                               |
|                                      | * |                               |
+--------------------------------------+---+-------------------------------+
| > Draft Data Collection and Analysis |   | > April 2008                  |
| > Plan                               |   |                               |
+--------------------------------------+---+-------------------------------+
| > Final Data Collection and Analysis |   | > May 2008                    |
| > Plan                               |   |                               |
+--------------------------------------+---+-------------------------------+
| > OMB Data Collection Package        |   | > May 2008                    |
| > Submitted                          |   |                               |
+--------------------------------------+---+-------------------------------+
| > Survey Data Collection             |   | > September 2008 -- December  |
|                                      |   | > 2008                        |
+--------------------------------------+---+-------------------------------+
| > Extant Data Retrieval              |   | > January 2008 -- December    |
|                                      |   | > 2008                        |
+--------------------------------------+---+-------------------------------+
| > Report on Completion of Data       |   | > February 2009               |
| > Collection                         |   |                               |
+--------------------------------------+---+-------------------------------+
| > First Draft Study Report           |   | > June 2009                   |
+--------------------------------------+---+-------------------------------+
| > Final Study Report                 |   | > July 2009                   |
+--------------------------------------+---+-------------------------------+
| > Draft Data File and Documentation  |   | > December 2009               |
+--------------------------------------+---+-------------------------------+
| > Final Data File and Documentation  |   | > March 2010                  |
+--------------------------------------+---+-------------------------------+

[]{.mark}

[]{.mark}

[]{#__RefHeading___Toc202088895 .anchor}A17. Approval To Not Display
Expiration Date

The expiration date for OMB approval will be displayed on the survey
forms. No exemption is requested.

[]{#__RefHeading___Toc202088896 .anchor}A18. Exceptions to the
Certificate Statement

The submission describing data collection requires no exemptions to the
Certificate for Paperwork Reduction Act (5 CFR 1320.9).

[]{#__RefHeading___Toc202088897 .anchor}References

Dillman, D. A. (2000). *Mail and internet surveys: The tailored design
method*. New York, NY: J. Wiley.

Edwards, P., Roberts, I., Clarke, M., DiGuiseppi, C., Pratap, S., Wentz,
R., et al. (2002). Increasing response rates to postal questionnaires:
Systematic review. *British Journal of Medicine, 324*, 1184-1191.

Kish, L. (1965). *Survey Sampling*. New York, NY: John Wiley & Sons,
Inc.

Markovitz, J., Cason, E., Frey, W., Riley, J., Shimshak, A., Heinzen,
H., et al. (2006). *Preschoolers\' Characteristics, Services and
Results: Wave 1 Overview Report from the Pre-Elementary Education
Longitudinal Study (PEELS)*. Rockville, MD: Westat.

Schiller, E., Fritts, J., Bobronnikov, E., Fiore, T., O\'Reilly, F., &
St. Pierre, R. (2006). *Volume I: The SLIIDEA Sourcebook Report
(1999-2000, 2002-2003, 2003-2004, and 2004-2005 School Years)*.
Cambridge, MA: Abt Associates, Inc.

U. S. Department of Labor. (2005). *The National Compensation Survey*.
Retrieved March 14, 2008, from www.bls.gov/ncs/home.htm#overview.

[^1]: The other three studies include: (1) analyses of extant data on
    special education; (2) a study of the impact of NLCB requirements on
    schools in need of improvement as a result of students with
    disabilities not meeting AYP requirements; and (3) an impact study
    of the implementation of Response to Intervention policies included
    in IDEA 2004.

[^2]: The Study of State and Local Implementation and Impact of IDEA (or
    SLIIDEA) was a longitudinal study collecting data from states in
    1999 -- 2000, 2002-2003, 2003-2004, and 2004-2005. District surveys
    were administered in 1999-2000, 2002-2003, and 2004- 2005.