Child and Adult Care Food Program 

(CACFP) 

Assessment 

of 

Sponsor Tiering Determinations 

2006 

Tiering Level
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and employer. 
Child and Adult Care Food Program (CACFP) 

Assessment of Sponsor Tiering 

Determinations 2006 

Authors:

From Macro International Inc.: 

Erika Gordon, Francine Barrington, 

Pedro J. Saavedra and JoAnn Kuchak 

Submitted by: Submitted to:

Macro International Inc. Office of Research, Nutrition, and Analysis 

11785 Beltsville Drive, Suite 300 USDA, Food and Nutrition Service 

Calverton, MD 20705 3101 Park Center Drive, Room 1014 

 Alexandria, VA 22302-1500 

Project Director: Project Officer: 

Erika Gordon Fred Lesnett 

 

This study was conducted under Contract number GS-23F-9777H with the Food and Nutrition Service. 

This report is available on the Food and Nutrition Service website: www.fns.usda.gov/oane.

Suggested Citation:

U.S. Department of Agriculture, Food and Nutrition Service, Office of Research, Nutrition, and Analysis, 

Child and Adult Care Food Program (CACFP) Assessment of Sponsor Tiering Determinations 2006, by 

Erika Gordon, Francine Barrington, Pedro J Saavedra and JoAnn Kuchak. Project Officer, Fred Lesnett 

Alexandria, VA: March 2008. 

United States Food and 

Department of Nutrition 

Agriculture Service 

March 2008

Special Nutrition Programs

Report No. CN-07-TD
i 

TABLE OF CONTENTS 

EXECUTIVE SUMMARY ..............................................................................................................1

CHAPTER 1. INTRODUCTION TO THE STUDY........................................................................5

CHAPTER 2. ASSESSMENT DESIGN AND METHODOLOGY.................................................7

Stage One Verification: Establishing Procedures to Verify the Current Tiering Status of FDCHS..............7

Procedures for Verifying Tier I Status..............................................................................................7

Verifying Tier II Status....................................................................................................................12

Stage Two Verification: Approach for Investigating Procedural Errors—Cases Where the Documentation 

Supporting the Tiering Determination Is Incomplete or Inconclusive ............................................12

Developing a Sampling Design: Constructing a Sample ............................................................................15

Estimating the Share of Misclassified FDCHs ............................................................................................16

Estimating the Share of Meals Affected In Misclassified FDCHs ...............................................................17

Annual Estimates of Under- and Over-Payments because of Misclassifications ..........................18

Estimating Upper and Lower Bounds of the Misclassification Rate ..............................................20

CHAPTER 3. THE DATA COLLECTION PROCESS ...............................................................21

Overview of the Data Collection Instrument Used for the Study.................................................................21

Training of the Data Collectors ......................................................................................................21

Arranging for Site Visits..................................................................................................................22

Collecting Data at Sponsor Administrative Sites ...........................................................................23

Creating the Data Analysis File......................................................................................................24

Data Validation Procedures ...........................................................................................................24

CHAPTER 4. RESULTS OF DATA COLLECTION, VALIDATION, AND ANALYSIS .............26

Tier I Share of FDCHs and Meal Reimbursements ....................................................................................26

Results of the Independent Two-Stage Validation Approach of Tiering Determinations with 

Procedural Misclassifications.........................................................................................................30

Procedures Used to Verify the Eligibility of FDCHs with Procedural Misclassifications .............................32

Primary Validation of Procedural Misclassifications in the Original Tiering Method: 

Using the School Boundary Method to Verify Tier I Status............................................................34

Results after Incorporating the Primary Independent Verification of Procedural 

Misclassification .............................................................................................................................36

Costs of Misclassifications after the Primary Validation of Procedural Errors...............................38

Secondary Validation of Remaining Procedural Misclassifications in the Original Tiering 

Method: Using the Census Block Group Method to Verify Tier I Status........................................41

Secondary Validation of Procedural Misclassifications: School Boundary...................................41

Secondary Validation of Procedural Misclassifications: Provider Income .....................................42

Secondary Validation of Procedural Misclassifications: Categorical Eligibility ..............................42

Secondary Validation of Procedural Misclassifications: Census Method ......................................42

Results after Incorporating the Secondary Independent Verification of Procedural 

Misclassifications ...........................................................................................................................43

Costs of Misclassification After the Secondary Verification of Procedural Errors.......................................45 

CHAPTER 5.CONCLUSION.......................................................................................................................48
ii 

EXHIBITS 

Exhibit A: Estimated Misclassification Rates by Tiering Status in FY 2006....................................3

Exhibit B: Costs of Verified Misclassifications in FY 2006................................................................4

Exhibit C: Meals and Expenditures Reimbursed at Tier I and Tier II Rates.....................................4

Exhibit 2.1: Sample Selected by Sampling Level................................................................................15

Exhibit 2.2: Share of Tier I Meal Types at Tier II FDCHs by State .....................................................17

Exhibit 4.1 Share of FDCHs Classified as Tier I by their Sponsors by State, Before 

Data Validation ...................................................................................................................27

Exhibit 4.2: Meals and Expenditures Reimbursed at Tier I and Tier II Rates...................................27

Exhibit 4.3: Basis of Tier I Qualification and Procedural Misclassification Rates—Original 

Data Collection Sponsor Files..........................................................................................28

Exhibit 4.4: Causes of Tier I Procedural Misclassifications ..............................................................30

Exhibit 4.5 Procedural Misclassification and Documentation Failure: Identifying Cases for 

Verification Follow-up .......................................................................................................32

Exhibit 4.6: Total Number of FDCHs with Unsupported Documentation—Procedural 

Misclassifications and Cases Confirmed as Tier I through the Primary and 

Secondary Validation Procedures ...................................................................................33

Exhibit 4.7: Primary Verified Misclassification Rates by Tiering Method ........................................35

Exhibit 4.8: Primary Verified Misclassification Rates by Tiering Status ..........................................36

Exhibit 4.9: Comparison of Procedural to Primary Verified Errors for Sampled FDCHs................36

Exhibit 4.10: Causes of Primary Verified Misclassification for Tier I FDCHs.....................................37

Exhibit 4.11: Primary Verified Tier I Misclassification Rate by State..................................................38

Exhibit 4.12: Comparison of Estimated Costs of Improper Payments for All FDCHs, 

2005 and 2006, After Primary Verification of Procedural Errors...................................39

Exhibit 4.13: Costs of Misclassifications after Primary Verification Procedures..............................40

Exhibit 4.14: Annual Number of Meals Served and Number of Meals Reimbursed at 

Incorrect Rate by FDCH Tier Type, after Primary Verification Procedures .................41

Exhibit 4.15: Misclassification Rates by Tiering Method, Secondary Verification Procedures.......43

Exhibit 4.16: Secondary Verified Misclassification Rates by Tiering Status .....................................43

Exhibit 4.17: Comparison of Procedural to Verified Errors for Sampled FDCHs, 

Primary and Secondary Validation Procedures..............................................................44

Exhibit 4.18: Verified Tier I Misclassification Rate by State ................................................................44

Exhibit 4.19: Comparison of Estimated Costs of Improper Payments for All FDCHs, 

2005 and 2006.....................................................................................................................45

Exhibit 4.20: Costs of Misclassifications...............................................................................................46

Exhibit 4.21: Annual Number of Meals Served and Number of Meals Reimbursed at Incorrect 

Rate by FDCH Tier Type....................................................................................................47
iii 

APPENDICES

APPENDIX 1. TABLES

Table A1.1: Sample of States...................................................................................... A-1

Table A1.2: Monthly Adjustments for Seasonality ................................................... A-2

Table A1.3: Maximum Months of Available Meal Counts......................................... A-3

Table A1.4: Sponsor Tier I Classifications and Misclassification Rates ................ A-4

APPENDIX 2. ASSUMPTIONS IN SAMPLE SELECTION AND WEIGHTING 

PROCEDURES ................................................................................................. A-7

Exhibit A2.1: The Expectation of the Number of Homes Selected per Region......... A-8

Exhibit A2.2: State Sampling Procedure and the Resulting Sample of States....... A-10

APPENDIX 3. TIERING DETERMINATION INSTRUMENT................................................... A-16

APPENDIX 4. EXAMPLES OF POOR DOCUMENTATION OF TIER I STATUS

Example 1: No Date on School Map Provided in FDCH File.................................. A-24

Example 2: Date on School Map in the FDCH Prior to 2002 .................................. A-25

Example 3: Unofficial School Map in FDCH File, with 

No Signed Supporting Documentation................................................ A-26

Example 4: School Linking to FDCH is FRP Ineligible........................................... A-27

Example 5A: Self-Reported Ledger Sheet ................................................................. A-28

Example 5B: Self-Reported Ledger Sheet ................................................................. A-29

Example 6: Self-Declared Ledger Sheet .................................................................. A-30
1 

EXECUTIVE SUMMARY 

The Improper Payments Information Act of 2002 (Public Law 107-300) requires all Federal 

agencies to calculate the amount of erroneous payments in Federal programs and to 

periodically conduct detailed assessments of vulnerable program components. This study of 

the Family Day Care Home (FDCH) component of the U.S. Department of Agriculture’s (USDA) 

Child and Adult Care Food Program (CACFP) developed and conducted a program assessment 

for producing a national estimate of the share of CACFP FDCHs that are misclassified into the 

wrong reimbursement tier. Misclassifications translate into improper payments because 

misclassified FDCHs do not receive the appropriate level of reimbursement for the meals and 

snacks provided to the children. As in the initial 2005 study, the purpose of the 2006 study is to 

identify erroneous payments arising from the misclassification of FDCHs for Tier I or Tier II 

program reimbursements. 

To develop national estimates of erroneous payments in this program component, the study 

drew a nationally representative sample of sponsor files for 3,150 Tier I and II FDCHs from 92 

distinct sponsors in 14 States. This represented approximately 2 percent of all FDCHs and 

10 percent of all sponsors. Data collectors went to each of these sponsors with randomly drawn 

lists of 30 to 90 FDCHs and extracted meal counts and tiering decision information from the 

sponsors’ files. In addition to information on tiering, information was collected on the number of 

meals reimbursed by tier type (Tier II FDCHs can be reimbursed at Tier I rates for the meals of 

individual children who are income eligible.), meal type, and month, from October 2005 through 

September 2006. 

The analysis of the data collected for each FDCH produced a determination of what tiering level 

the documents supported and what tiering level the sponsor had designated. Whenever there 

was a discrepancy between these two determinations, a procedural misclassification was 

identified.1

 Almost 20 percent of all FDCH homes had a procedural misclassification (i.e., their 

file documentation did not support the tiering determination). 

Slightly more than 77 percent of procedural misclassifications were attributable to errors in the 

school boundary method for determining Tier I status, including inadequate documentation 

linking an FDCH to an eligible school or inadequate documentation of an eligible school. 

Independent validation procedures were used to confirm the Tier I status of FDCHs with 

procedural errors related to school boundary, provider income, categorical eligibility, and the 

Census tiering determination methods. The independent validation only reviewed the 

documentation present in the FDCH sponsor file, and was limited to using the existing 

documentation to determine if the Tier I status could be supported by using either the school 

boundary method, the primary validation method, or by using the Census block group method, 

the secondary validation method. The Census block group method was only attempted in cases 

where the school boundary method resulted in either an inconclusive or lower tiering status 

determination.2

 After these procedures, 97.08 percent of all homes were found to be correctly 

 

1 A procedural error may or may not lead to an improper payment; the latter are addressed later in this document. 2

 It should be noted that the school boundary method was attempted first in the independent verification procedures 

for all tiering methods except for those cases where the original tiering status was determined using the Census block 

group method. In this instance, the original method was first attempted independently and then the school boundary 

method was attempted. This ordering is outlined in the algorithms presented in Chapter 3 of this report. 
2 

classified. The rate of misclassification was determined to be 2.92 percent for all FDCHs and 

4.03 percent for Tier I homes (see Exhibit A). 

Exhibit B shows the estimated costs associated with the verified estimates of misclassifications, 

including findings from both the primary and secondary validation processes. The total amount 

of improper payments3

 associated with misclassified FDCHs for this study is estimated to be 

$9.4 million, with a 90 percent confidence range of between $6.5 and $12.2 million; which 

represents 1.4 percent of the total FDCH meal reimbursements in 2006. 

The total estimated expenditures for meal reimbursements for all homes (covering the period 

from October 2005 to September 2006) were $671,764,329 (Exhibit C). 

 

3

 That is, the sum of the overpayments to Tier I homes and the absolute value of the underpayments to Tier II homes. 
3 

Exhibit A: Estimated Misclassification Rates by Tiering Status in FY 2006 

Type 

of Home 

Pre-Verification 

Estimate of 

Misclassification 

Rate 

Lower 

Limit* 

Upper 

Limit* 

PreVerification 

Estimate of 

FDCHs 

Incorrectly 

Classified** 

PreVerification 

Estimate of 

FDCHs 

Correctly 

Classified 

Estimated 

Total 

FDCHs 

Tier I 27.48% 23.80% 31.20% 28,419 74,989 103,408***

Tier II 0.22% 0.10% 0.40% 94 42,790 42,884***

All Tier I or 

Tier II 

19.49% 17.50% 21.50% 28,512 117,779 146,292 

Type 

of Home 

Preliminary 

Verified 

Estimate of 

Misclassification 

Rate 

Lower 

Limit* 

Upper 

Limit* 

Preliminary 

Verification 

Estimate of 

FDCHs 

Incorrectly 

Classified 

Preliminary 

Verification 

Estimate of 

FDCHs 

Correctly 

Classified 

Estimated 

Total 

FDCHs 

Tier I 4.78% 3.46% 6.10% 4,944 98,464 103,408***

Tier II 0.22% 0.08% 0.36% 94 42,790 42,884***

All Tier I or 

Tier II 

3.44% 2.65% 4.23% 5,038 141,255 146,292 

Type 

of Home 

Final Verified**** 

Estimate of 

Misclassification 

Rate 

Lower 

Limit* 

Upper 

Limit* 

Secondary 

Verification 

Estimate of 

FDCHs 

Incorrectly 

Classified 

Secondary 

Verification 

Estimate of 

FDCHs 

Correctly 

Classified 

Estimated 

Total 

FDCHs 

Tier I 4.03% 2.76% 5.31% 4,171 99,237 103,408***

Tier II 0.22% 0.08% 0.36% 94 42,790 42,884***

All Tier I or 

Tier II 

2.92% 2.14% 3.69% 4,265 142,027 146,292 

 * 90 percent confidence level: ** All sampled FDCHs for which Tier I status cannot be documented, either initially or through follow 

up, are deemed incorrectly classified. ***Total homes estimated from sample. Source: 2006 CACFP Tiering Assessment, weighted 

estimates. Final Verified findings include the outcomes of the secondary verification of FDCHs with procedural errors using primarily 

the Census block group method. 
4 

Exhibit B: Costs of Verified Misclassifications in FY 2006 

Primary Verification**** 

Estimated 

Costs* 

Lower Bound 

Estimate** 

Upper Bound 

Estimate** 

Estimated 

Total 

FDCHs 

Misclassified Tier I FDCHs $11,249,292 $8,301,852 $14,196,731 103,408*** 

Misclassified Tier II FDCHs $146,852 $77,938 $215,765 42,884*** 

All Misclassified FDCHs $11,396,144 $8,441,351 $14,350,936 146,292 

Secondary Verification**** 

Estimated 

Costs* 

Lower Bound 

Estimate** 

Upper Bound 

Estimate** 

Estimated 

Total 

FDCHs 

Misclassified Tier I FDCHs $9,206,139 $6,407,469 $12,004,810 103,408*** 

Misclassified Tier II FDCHs $146,852 $77,938 $215,765 42,884*** 

All Misclassified FDCHs $9,352,991 $6,547,135 $12,158,847 146,292 

* Cost estimates are the seasonally adjusted expected values where the expectation takes into account the average number of 

meals and snacks for which a Tier II home would be compensated at the highest (Tier I) level. ** 90 percent confidence level. 

***Total homes estimated from the sample. Source: 2006 CACFP Tiering Assessment. ****Data for Primary Verification presents 

the findings after the initial wave of independent follow-up of procedural errors using the school boundary method had been 

conducted. Secondary Verification represents the findings after the Census block group method had been attempted on the 

remaining procedural errors. 

Exhibit C: Meals and Expenditures Reimbursed at Tier I and Tier II Rates 

Number of Meals 

and Snacks Expenditures 

Share of Meals 

and Snacks 

Share of 

Expenditures 

Tier I 477,872,447 $586,774,703 77% 87% 

Tier II 144,753,831 $84,989,626 23% 13% 

Total 622,626,278 $671,764,329 100% 100% 

Source: 2006 CACFP Tiering Assessment. National, weighted, seasonally adjusted estimates based on sponsor files 

for 3,150 FDCHs. 
5 

CHAPTER 1. INTRODUCTION TO THE STUDY 

The U.S. Department of Agriculture’s (USDA’s) Child and Adult Care Food Program (CACFP) 

plays a vital role in improving the quality of day care by reimbursing providers for their costs of 

meals and snacks. Each day, 2.9 million children receive nutritious meals and snacks through 

CACFP.4

 USDA’s Food and Nutrition Service (FNS) administers CACFP by means of grants to 

States, typically State educational agencies. Independent centers and sponsoring organizations 

enter into agreements with State agencies to assume administrative and financial responsibility 

for CACFP operations. 

Since the establishment of CACFP in 1968 (Section 17 of the National School Lunch Act 

[42 U.S.C. 1766]), the number of children served has grown and the method of compensating 

meals has changed. Participation was originally limited to center-based child care in areas 

where poor economic conditions existed. In 1976, family day care homes (FDCHs) also 

became eligible to participate, provided they met State-licensing requirements or otherwise 

obtained approval from an appropriate State or local agency. Rather than have FDCHs apply 

directly to State agencies, they were required to be sponsored by a public or private nonprofit 

organization that assumed responsibility for ensuring compliance with Federal and State 

regulations and acted as a conduit for meal reimbursements.5

The Personal Responsibility and Work Opportunity Reconciliation Act of 1996 (PRWORA) 

changed the meal reimbursement structure for FDCHs, establishing two tiers of reimbursement 

rates (Tier I and Tier II). The intent of this change to CACFP was to target program benefits 

more closely to low-income children. Now, FDCHs in low-income areas or those operated by 

low-income persons meeting the guideline of being at 185 percent below the poverty line are 

classified as Tier I and are reimbursed for meals at higher rates than all other FDCHs, referred 

to as Tier II FDCHs. All other homes, referred to as Tier II homes, are reimbursed at lower 

rates, meaning they receive less money per meal served. Tier II FDCHs can still receive the 

higher Tier I reimbursement rates for meals served to children from families with incomes at or 

below 185 percent of the poverty level, but the individual child’s eligibility must be documented. 

Sponsoring organizations are responsible for determining that FDCHs meet CACFP eligibility 

criteria, providing training and other support, designating each FDCH as either Tier I or Tier II, 

and monitoring the FDCHs to ensure that they comply with applicable Federal and State 

regulations. Sponsors receive and verify the claims of FDCHs for CACFP reimbursement, 

forward the claims to their State CACFP offices, receive the reimbursements, and distribute the 

meal reimbursements to the FDCHs. 

The Improper Payments Information Act of 2002 (Public Law 107-300) requires Federal 

agencies to identify and reduce erroneous over- and under-payments in various programs, 

including CACFP. 

 

4

 Another 86,000 adults are served. 

5

 The CACFP Website (http://www.fns.usda.gov/cnd/Care/CACFP/cacfpfaqs.htm) presents a detailed history of the 

changes in program participation and rules. 
6 

As in the Base year study in 2005,6 the purpose of this study is to identify erroneous payments 

arising from the misclassification of FDCHs for Tier I or Tier II program reimbursement.7

 

Specifically, the objectives of the study are to— 

1. Develop the program assessment design and methodology for producing nationally 

representative estimates of the number of FDCHs participating in CACFP that have been 

assigned an incorrect tiering status. 

2. Collect the required data to develop nationally representative estimates of FDCHs 

participating in CACFP that have been assigned an incorrect tiering status. 

3. Report an estimated range from the highest to the lowest likely amount of the cost, in 

terms of misallocated meal/snack reimbursements, of misclassifying FDCHs as Tier I as 

well as the underpayments associated with inaccurate Tier II designations. 

The remainder of this report presents the assessment design and methodology, a discussion of 

the data collection procedures, analysis outcomes, and study findings. 

 

6

 Child and Adult Care Food Program (CACFP): Assessment of Sponsor Tiering Determinations, 2005 Final Report. 

7

 FNS has been conducting a comprehensive onsite assessment of a sample of participating FDCH sponsors to 

review compliance with recordkeeping requirements and supportability of claims for meal reimbursement by FDCHs. 
7

CHAPTER 2. ASSESSMENT DESIGN AND METHODOLOGY 

The purpose of this chapter is to explain in depth the procedures that were adopted to meet the 

study design objectives. The assessment design employed in this study was based on the 

design used in the 2005 study, where the key methodological tasks were (1) establishing a 

procedure to verify the current tiering status of FDCHs as they are listed in sponsors’ files, 

(2) developing a sampling design to estimate the misclassification rate within an upper and 

lower bound of 2.5 percentage points at the 90 percent confidence level, and (3) estimating the 

upper and lower bound of the amount of overpayments associated with misclassified Tier I 

FDCHs and underpayments associated with misclassified Tier II FDCHs. 

In the 2005 study, the analysis of preliminary findings revealed the need for validation8

 activities 

to be conducted in cases where the tiering determination documentation was ambiguous and 

did not clearly support the original tiering determination. To address this methodological need, 

a series of algorithms were developed to validate sponsors’ tiering determinations. The 

assessment plan for determining tiering misclassification was expanded to a two-stage 

approach to allow for follow-up verification procedures for cases where there is an initial 

misclassification resulting from insufficient or incomplete documentation at the sponsor level 

(procedural misclassifications). These algorithms, providing for alternative means of validating 

a tiering decision, are presented as a part of this discussion as well. The discussion begins by 

reviewing the necessary criteria for establishing procedures to verify the current status of 

FDCHs determined by sponsors, before presenting a discussion of the other major 

characteristics of the assessment design. 

STAGE ONE VERIFICATION: ESTABLISHING PROCEDURES TO VERIFY THE 

CURRENT TIERING STATUS OF FDCHS 

Procedures for Verifying Tier I Status

The assessment design for the study was based directly on the regulations set forth in 7 C.F.R. 

§226.2. The definitions of tiering status are as follows: 

Tier I day care home means (a) a day care home that is operated by a provider whose 

household meets the income standards for free or reduced-price meals, as determined by the 

sponsoring organization based on a completed free and reduced-price application, and whose 

income is verified by the sponsoring organization of the home in accordance with §226.23(h)(6); 

[The quoted definition does not mention that a day care home operated by a provider currently 

participating in a Government means-tested program in which the income of the provider’s 

household is less than 185 percent of the poverty level is deemed categorically eligible for Tier I 

reimbursements.] (b) A day care home that is located in an area served by a school enrolling 

elementary students in which at least 50 percent of the total number of children enrolled are 

certified eligible to receive free or reduced-price meals; or (c) A day care home that is located in 

a geographic area, as defined by FNS based on Census data, in which at least 50 percent of 

the children residing in the area are members of households that meet the income standards for 

free or reduced-price meals. 

 

8

 In this report, the term validation is used to refer to activities conducted to assess the inadequacy of sponsor 

documentation and check alternatives for documenting the tiering status of an FDCH. The term verified is used to 

refer to the conclusion and results of this follow-up process. 
8

A Tier II day care home means a day care home that does not meet the criteria for a Tier I day 

care home. Sponsors are responsible for the determination of the tiering level of each FDCH.9

 

There are two broad methods for FDCH tier determination status in CACFP: 1) Area Eligibility or 

2) Income Eligibility. Area Eligibility methods rely on the geographic location of the provider in 

an area where at least 50 percent of the total number of children residing in the area lives in a 

household that meets the income standards for free or reduced-price meals. Proof of Area 

Eligibility can be shown in one of two ways— 

1. School Boundary Area: The provider must be served by a school enrolling elementary 

students in which at least 50 percent of the total number of children enrolled is certified 

eligible to receive free or reduced-price meals. 

2. Census Block Group: The provider must be located in a Census block group in which at 

least 50 percent of the total number of children residing in the area live in a household that 

meets the income standards for free or reduced-price meals.10

In contrast, Income Eligibility methods rely on proof that household income of the FDCH 

provider meets the criteria for free or reduced-price school meals (185 percent of Federal 

poverty guideline or below), and can be achieved through two means— 

1. Provider’s Documented Annual Income: A completed income eligibility statement for the 

provider that lists all household members and associated income. (Sponsors are required 

to verify income eligibility information through such documents as pay statements and tax 

returns from households). 

2. Categorical Eligibility: The FDCH provider is currently participating in a Government 

means-tested program that has a household income eligibility level less than or equal to 

185 percent of the Federal poverty level (e.g., the Food Stamp, TANF, or Food Distribution 

Program on Indian Reservation [FDPIR] programs. 

 

9

 The tiering determination is one of the primary responsibilities of sponsors, which make the decision based on 

official guidelines found in the FNS guidance (Child and Adult Care Food Program: Eligibility Guidance for Family Day 

Care Homes) that details the requirements for Tier I status. 10 There may be some confusion about using the Census approach to establish Tier I status because of the 

instructions in FNS’s Child and Adult Care Food Program: Eligibility Guidance for Family Day Care Homes. In a 

section entitled “Questions & Answers About Classification of Family Day Care Homes,” the third question is: “If there 

is a conflict between Census data and elementary school free and reduced price enrollment data, how should a 

determination be based?” The answer on page 18 is: “Census block group data should not be used when relevant, 

current-year information on free and reduced price eligibility in neighborhood elementary schools is available.” This 

answer mirrors the discussion on pages 6 and 7 of FNS’s CACFP document where the use of Census data is limited 

to relatively few situations (rural area, magnet school, and local area does not reflect elementary school conditions). 

However, §226.15 (f) states: 

Day care home classifications. Each sponsoring organization of day care homes shall determine which 

of the day care homes under its sponsorship are eligible as Tier I day care homes. A sponsoring 

organization may use current school or Census data provided by the State agency or free and reduced 

price applications collected from day care home providers in making a determination for each day care 

home. When using elementary school or Census data for making Tier I day care home determinations, 

a sponsoring organization shall first consult school data, except in cases in which busing or other bases 

of attendance, such as magnet or charter schools, result in school data not being representative of an 

attendance area’s household income levels. This directive only requires that sponsors check school 

data; they may use Census data even if relevant school data are available. 
9

An FDCH can be classified as a Tier I home on the basis of one of three grounds— 

1. If the income of the proprietor is less than 185 percent of the poverty line 

(Income Eligibility). 

2. If a home is located in the catchment area of an elementary school in which at least 

50 percent of the students are eligible for free and reduced-priced meals 

(Area Eligibility—School). 

3. If the home is in a Census tract in which at least 50 percent of the children under 13 years 

old are in families with household income at or below 185 percent of the poverty line (Area 

Eligibility—Census). 

A Tier I designation is only valid for a limited period (depending on the method of qualification). 

In June 2004, homes that were classified as Tier I homes on the basis of Area Eligibility—

School could keep this classification for 5 years (previously, it had been for 3 years). By 

contrast, Tier I homes that are classified on the basis of proprietor’s income must be reviewed 

every year. Finally, Tier I classifications on the basis of Census information are valid until the 

next Census data are available. FNS does not require sponsors to make changes in Area 

Eligibility during these periods even if there is reason to believe that there has been a change in 

status. In contrast, a Tier II designation never has to be reviewed unless the FDCH requests a 

review of its status. 

There are only two types of FDCHs (Tier I or Tier II). Any FDCH that does not qualify as a Tier I 

FDCH is automatically a Tier II FDCH. For each of the tiering determination methods, various 

documents can be used to prove eligibility. Therefore, each approach requires a detailed listing 

of the necessary dated documents that must be present in the sponsor’s file for an FDCH to be 

properly classified as Tier I. Each of these four approaches or “algorithms” is explained in detail 

below. 
10

Area Eligibility: School Boundary Area 

The following algorithm specifies the evidence considered acceptable for determining11 Tier I 

area eligibility on the basis of local elementary school boundary data. 

1. The tiering decision was made after Oct 1, 2002.12 

2. The FDCH provider’s address must be linked to a specific school. All of the following were 

acceptable forms of documentation: 

• A dated official school boundary-identifying map 

• Pages from a dated address directory linking the FDCH’s address to a specific 

elementary school 

• A dated and signed letter from a local school official indicating that the FDCH’s 

address is served by the school 

• A report (initialed and dated) of a phone call to a school official indicating that the 

FDCH’s address is served by the school 

• A printed copy of a Website linking addresses to specific elementary schools; some 

form of dating must be present. 

3. The named school must have at least 50 percent of its students eligible for free or 

reduced-price meals. Acceptable documentation includes the following: 

• A dated State master list of schools indicating which elementary schools are eligible or 

showing the percentage of children receiving free and reduced-price meals 

• A dated and signed letter from a local school official indicating that at least 50 percent 

of enrolled children are eligible for free or reduced-price meals. 

4. If there was no documentation in the file about the share of students at the listed school 

eligible for free and reduced-price meals, the lists provided by the States identifying 

whether the elementary school met the eligibility standard were checked. 

Area Eligibility: Census Block Group 

The following algorithm specifies the evidence considered acceptable for determining Tier I area 

eligibility on the basis of Census block group data. 

1. Documentation that the address lays within a specific block group. Acceptable 

documentation includes an official map, output from a geo-mapping computer program, or 

output linking specific addresses and Census block groups. 

 

11 In one State in this study, the State agency, rather than the sponsors, determined the tiering status on the basis of 

school and census eligibility. While this is inconsistent with the CACFP rule that the sponsors have to determine 

eligibility, FNS instructed that the State determinations be accepted as valid even though there was no 

documentation onsite in the sponsors’ files. 12 The change in the standard from 3 to 5 years for the duration of valid school catchment area-based tiering 

determinations means that all FDCHs tiered in June 2004, with the proper supporting documentation, have a valid 

tiering date for the next 5 years. However, the study is following last year’s methodology in reviewing those FDCHs 

that have a tiering determination date prior to June 2004. The previous year’s study identified the baseline date for a 

valid tiering determination as occurring 3 years before the beginning of the data collection window, June 1, 2001. 

FDCHs tiered under the old guidelines, with the proper supporting determination, would have been valid at the data 

collection point of June 2004 in the original study. For the current study, applying this method results in a date of 

October 2002, 3 years before the beginning of the current study’s data collection window (October 2005). 
11

2. Documentation that 50 percent of children under 13 years old within the block group live in 

households with income less than or equal to 185 percent of the Federal poverty level. 

Income Eligibility: Provider Income 

The following algorithm specifies the evidence considered acceptable for determining Tier I 

income eligibility on the basis of provider’s income, which must be less than or equal to 

185 percent of the Federal poverty level for the number of people in the household. 

1. A signed and dated application (equivalent to the free and reduced-price meals benefit 

form). This form must have contained the provider’s Social Security Number and been 

filled out after October 1, 2005 (based on the data window for the current study). 

2. A listing of all of the sources of income for each member of the household with income. 

Income from retirement accounts or from child care payments was included. 

3. No business loss can be used to offset other sources of income. 

4. Each income source must be dated to show that it documented income from April 1, 2005 

on.13 However, tax forms for 2004 were acceptable as long as the provider indicated that 

the information on the return reflects current household income. 

5. Each income source had to be dated and validated by one of the following: 

• Tax Forms 1040 or Schedule C (for business income from running an FDCH) 

• Recent pay stub 

• Letter from employer 

• Ledger or tax books 

• Benefit award letter 

• Court decree or divorce agreement (for child support) 

• Bank statement (for direct deposit of Social Security or other monthly 

retirement check) 

• Copy of checks to document benefits or child support/alimony. 

Income Eligibility: Categorical Eligibility 

The following algorithm specifies the evidence considered acceptable for determining Tier I 

income eligibility on the basis of the provider’s eligibility for other Government means-tested 

programs. 

1. All forms had to be dated after April 1, 2004. 

2. A certification, letter, or printout of a Temporary Assistance for Needy Families (TANF) 

State program award letter showing that the provider was eligible for TANF benefits at the 

time of tiering evaluation. 

3. A certification, letter, authorization card, or printout showing that the provider was eligible 

for Food Stamp benefits at the time of tiering evaluation. 

 

13 For this year’s study, the most recent tax forms would be from year 2005. These forms could be filed anytime 

between January 1, 2005 and April 2005. However, when present tax forms dated from 1/12004 were accepted as 

valid, given the form was signed and dated. 
12

4. A notice of eligibility for FDPIR showing that the provider was eligible for FDPIR benefits at 

the time of tiering evaluation. 

5. A certification, letter, authorization card, or printout showing that the provider was eligible 

for another qualifying Government income-based program at the time of tiering evaluation. 

Verifying Tier II Status

Because all FDCHs that are not designated as Tier I are designated as Tier II, no supporting 

documents are required for this designation. If upon entry to the program, an FDCH is certified 

as Tier II, sponsors are under no obligation to recertify the FDCH, unless the provider requests 

recertification to determine whether the FDCH qualifies as Tier I. To verify the status of Tier II 

FDCHs, the study used the following protocol: 

1. For each selected FDCH designated as Tier II by the sponsor, the onsite field data 

collector reviewed the sponsor’s records to determine the date of program certification. 

2. All the documents in the file that might be used to qualify the home for Tier I status were 

copied. These documents were then used to determine whether they were sufficient to 

qualify the home as Tier I. 

3. The onsite sponsor files were examined to determine if there was evidence that the FDCH 

requested re-certification. If this was true, an investigation was conducted to determine in 

which elementary school catchment area the FDCH was currently located. Once the 

FDCH-elementary school link was identified, the school was investigated using the State’s 

master list in the appropriate year to see whether the school qualified as having more than 

50 percent of its students being eligible for free and reduced-priced meals. 

STAGE TWO VERIFICATION: APPROACH FOR INVESTIGATING 

PROCEDURAL ERRORS—CASES WHERE THE DOCUMENTATION 

SUPPORTING THE TIERING DETERMINATION IS INCOMPLETE OR 

INCONCLUSIVE 

As previously described, the second stage of the tiering misclassification approach provided for 

follow-up assessment of the FDCHs assigned tiering level when the documentation in the 

sponsor’s file was found to be insufficient or inconclusive. Chapter 3 provides a detailed 

discussion of the enactment of these procedures. Here, the decision algorithms developed to 

address inconclusive or incomplete documentation supporting a tiering determination for each 

method of making the decision are presented. Each tiering determination method (Area—

School Boundary, Area—Census Block Group, Income—Categorical Eligibility, and Income—

Provider Income) had a specific algorithm that was developed to pursue other means of 

verifying the tiering determination. 

Area Eligibility: School Boundary Area 

For FDCHs assigned to a tiering level on the basis of the elementary school serving their area, 

the following procedures were developed: 

1. The existing documentation in the FDCH file was used to identify the local elementary 

school. In cases where the documentation did not indicate a local elementary school, 

Mapquest was used to identify the closest school, which was used as the starting point 
13

school for verification; or the State local education agency (LEA) was contacted to identify 

the nearest elementary school. 

2. The telephone numbers of the schools were obtained from the National Center for 

Educational Statistics Website or other Web-based sources. 

3. Each of the schools were called to verify that the FDCH was served by that school. The 

calls also verified that the elementary schools serving the FDCHs had at least 50 percent 

of their students eligible for a free or reduced-price meal. 

4. If a school representative indicated that that the FDCH was not in their attendance area, 

we asked for a suggestion of the proper school for this address. For this alternative 

option, the same contact procedures were followed until a definitive response was reached 

to confirm the FDCH location was within the school catchment area. If a new school was 

identified, the State list documenting those elementary schools having at least 50 percent 

of the students eligible for a free or reduced-price meal was cross-checked to verify that 

the newly identified school met the free and reduced priced meal guidelines. 

5. If the FDCH was unable to be verified using the school list, an attempt to validate the 

tiering determination using the Census block group method was made. 

6. The existing documentation was used to identify the address of the FDCH. 

7. The Census’ “FairData”14 database at Norfolk State University was used to query for the 

respective address by Census track. 

8. If the FDCH had an address in a Census track where less than 50 percent or more of the 

children under age 13 live in households at or below 185 percent of poverty, the FDCH 

was considered misclassified by this method. If it met the criteria for Census block group, 

it was assigned the tiering status supported by this method. 

9. If the follow-up verification of the school successfully resolved the status of the school, but 

resulted in a lower tiering status, the Census block group method was assessed for the 

tiering determination it would assign when possible. The tiering criteria (school or Census) 

that would assign the FDCH the tiering status with the highest level of reimbursement was 

adopted for the FDCH. 

Area Eligibility: Census Block Group 

For FDCHs assigned to a tiering level based on Census data where data was inconclusive (no 

record of the census block group on file), the following procedures were developed to verify the 

tiering status of the FDCH: 

1. The existing documentation in the FDCH file was used to identify the address of 

the FDCH. 

 

14 This interactive map was developed for local groups who need highly detailed (street-level) census information to 

identify neighborhoods and communities for Child and Adult Care Food Program sites. The default map shows 

percentage themes for the population under age 13 and below the 185% poverty level. The tool was developed by 

the Norfolk State University Dept. of Political Science, and uses Census 2000 adjusted data as the basis for the map 

generation. 
14

2. The Census’ “FairData” database was used to query for the respective address by 

Census track. 

3. If the FDCH had an address in a Census track where less than 50 percent or more of the 

children under age 13 live in households at or below 185 percent of poverty, the FDCH 

was considered misclassified as Tier I. 

4. If the validation procedure supported a tiering determination using this method that 

resulted in a lower tiering status than that originally assigned by the sponsor, the address 

was used to match the FDCH with a school to assess the tiering status based on that 

method. Once a school had been identified, the follow up investigation verified whether 

the identified school was on the respective State’s list of eligible schools having more than 

50 percent of its students being eligible for free and reduced-priced meals. If this link 

existed, the school method was used to determine the tiering status of the FDCH. 

5. The tiering criteria (school or census) that assigned the FDCH the tiering status with the 

highest level of reimbursement was adopted for the FDCH. 

Income Eligibility: Categorical Eligibility or Provider Income 

For FDCHs with inadequate income tiering documentation, either categorical or provider 

income, the following procedures were employed to verify the tiering status of the FDCH: 

1. We used sponsor documentation to identify the local elementary school. In cases where 

the documentation did not indicate a local elementary school, we used Mapquest or 

contacted the State LEA to identify the nearest elementary school. 

2. We then obtained the telephone numbers of the schools from the National Center for 

Educational Statistics Website or other Web-based sources. 

3. We made follow-up verification phone calls to determine whether these FDCHs were 

indeed served by elementary schools in which at least 50 percent of the students are 

eligible for a free or reduced-price meal. Each of the schools was called to verify that the 

address of the FDCH was served by that school. 

4. If a school representative indicated that the FDCH was not in their service area, we asked 

for a suggestion of the proper school for this address. For this alternative option, we 

followed the same contact procedures until a definitive response was reached. If a new 

school was identified, we also cross-checked our State lists of schools (in which at least 

50 percent of the students were eligible for a free or reduced-price meal) to verify its 

existence on this list. 

5. If the case’s tiering status was confirmed using the school method, but the tiering status 

was lower than the sponsor assignment, the case was reviewed using the Census block 

group method. 

6. Alternatively, if the FDCH was not verified using the school method, the case was 

reviewed using the Census block group method. 

7. If neither attempt at verification resulted in evidence supporting the sponsor’s Tier I 

determination for the FDCH, it was considered misclassified. 
15

8. However, if the FDCH was determined to meet the Census block group criteria, the case 

was verified as Tier I. In all cases, the tiering criteria that assigned the FDCH the tiering 

status with the highest level of reimbursement was adopted for the FDCH. 

DEVELOPING A SAMPLING DESIGN: CONSTRUCTING A SAMPLE 

For this study, a sampling strategy was required to produce national estimates of an error rate 

with 90 percent certainty for no greater than plus or minus 2.5 percentage points (i.e., if the 

results of the assessment indicated that 20 percent of all FDCHs were misclassified, then the 

computed confidence level with 90 percent certainty would lie between 17.5 and 22.5 percent). 

Appendix 2 provides a discussion of the statistical details of the sampling. 

To minimize any design effect, each FDCH had approximately the same probability of selection. 

The approach used produces approximately the same probability of selection for every FDCH 

while retaining a diversity of States. Exhibit 2.1 summarizes the sampling procedures that were 

used.15

On the basis of the data provided by FNS, 14 distinct States were sampled.16 For all of the 

States but California, 210 FDCHs were included in the sample. For California, 420 FDCHs were 

included in the sample. 

Exhibit 2.1: Sample Selected by Sampling Level 

Universe Guideline Sample

50 States

+ D.C. 14 States

908 sponsors

Generally

7 sponsors

per State 92 sponsors

146,292 FDCHs

Generally

210 FDCHs per State

or

30 FDCHs per sponsor

3,150 FDCHs

Universe Guideline Sample

50 States

+ D.C. 14 States

908 sponsors

Generally

7 sponsors

per State 92 sponsors

146,292 FDCHs

Generally

210 FDCHs per State

or

30 FDCHs per sponsor

3,150 FDCHs

Having selected the States, the next step was to select 7 sponsors from each State (except 

California, where 14 sponsors were selected). The sponsors within each State were chosen 

randomly on the basis of the number of FDCHs served by each sponsor. One sponsor had to 

be replaced when it was discovered that they had gone out of business and the records were 

inaccessible. 

 

15 The data supplied for sampling reflected the number of FDCH’s determined to be active in the third quarter of 2006, 

from FNS files. This was the most recent data available. It should be noted that in selecting the 92 unique sponsors 

for the sample, some did have the probability of being selected more than once due to their size. 16 The District of Columbia and Virginia were sampled as one unit in the study. 
16

The next step involved choosing the FDCHs to be included in the study. An FDCH was eligible 

for selection if it had been reimbursed for meals served during September 2006, the quality 

control month for this year’s study.17 For each sponsor, 30 FDCHs that had been active in 

September 2006 were randomly selected and an additional 11 FDCHs were selected as 

possible replacements. Some sponsors were so large that they were selected more than once. 

For sponsors that had been selected more than once, multiples of 30 FDCHs were chosen 

depending on the number of times the sponsor had been selected (see Appendix 2 for details). 

ESTIMATING THE SHARE OF MISCLASSIFIED FDCHS 

Once all of the data were entered into the analytic database (the creation of which is described 

in the next chapter), the tiering algorithm was applied and each FDCH was classified by Macro 

as either Tier I or Tier II. The validity of the documentation supporting an FDCH’s tiering 

determination was based on whether the study-determined tiering was the same as the one that 

appeared in the sponsor’s files. 

To develop a national estimate of the procedural (i.e., document-based) misclassification rate, 

the data collection process had to be reviewed to determine the weights to be assigned to each 

FDCH. Although the sampling design was developed to be approximately self-weighing, there 

were data inconsistencies between the various sources of information on the number of FDCHs 

per sponsor and per State. These differences reflected the fact that FDCH providers move in 

and out of the program. Consequently, the number of FDCHs per sponsor or per State was 

constantly changing.18 

These discrepancies meant that weights had to be developed for each sponsor to get the best, 

unbiased national estimate of misclassified FDCHs. See Appendix 3 for a more detailed 

discussion. 

The formula used to determine the percentage of misclassified FDCHs is presented in the 

following equation: 

(2.1) P(X) = 

∑=

3,150

i 1

i i w x

 divided by 146,29219, where 

xi is equal to 1 when FDCHi is misclassified, and 0 otherwise; 

wi is equal to the weighted probability of selection; and 

P(X) is the percentage of misclassified FDCHs 

 

17 Sponsors have up to 90 days to submit initial or revised meal counts, so September 2006 was the last month in 

which reliable, final data were available to the data collectors beginning in December of 2006. 

18 Depending on when the data were collected, State, national, and sponsor information can vary in three ways. First, 

in choosing States and sponsors, FDCH counts from FNS were used to select the States. However, the total number 

of FDCHs derived from the State list varied from the number derived from the national list. Second, a similar 

discrepancy arose in dealing with sponsors: Sponsors were chosen on the basis of the number of FDCHs that the 

State said the sponsor had. However, this number varied from the number of FDCHs on the sponsors’ lists. Third, 

when the data collectors appeared at the sponsors’ administrative headquarters with their lists of randomly chosen 

FDCHs, in a handful of cases a selected FDCH was found not to have been active in September 2006 and hence 

was ineligible to be in the sample. This was not a problem because replacement options were available, so the data 

collectors were able to extract information easily for the appropriate number of FDCHs at that sponsor site. However, 

discrepancies between State-supplied and sponsor-provided lists required further adjustment of weights. 19 This number is the number of homes used in the sample, obtained from FNS files. 
17

A similar computation was done separately for the 2,220 sampled FDCHs classified by 

sponsors as Tier I and the 930 sampled FDCHs classified as Tier II. 

ESTIMATING THE SHARE OF MEALS AFFECTED IN MISCLASSIFIED FDCHS 

Determining the cost of each misclassified FDCH required different approaches for Tier I and 

Tier II FDCHs. The cost of any misclassification took into account the fact that the meals of 

some children in Tier II FDCHs are reimbursed at Tier I rates. 

For Tier II FDCHs, a misclassification meant that all of the meals should have been reimbursed 

at Tier I rates. Therefore, the added cost of reimbursement at the higher, Tier I rate had to be 

applied to all of the meals that were originally reimbursed at Tier II rates. 

In misclassified Tier I FDCHs, the added costs only applied to the meals served to children who 

do not qualify individually for Tier I reimbursement rates, even if the FDCH was Tier II. 

However, there was no information available to determine how many children in each 

misclassified Tier I FDCH would qualify for the higher reimbursement rates. Consequently, an 

estimate of this number was developed on the basis of the experience of Tier II FDCHs in the 

State in which the FDCH was located. 

As Exhibit 2.2 shows, an estimated 15 to 16 percent of meals at Tier II FDCHs were reimbursed 

at Tier I levels. The variation across States, however, was quite large. In State 9, for example, 

between 7 and 8 percent of meals in Tier II FDCHs were compensated at the higher rate. In 

contrast, the corresponding numbers for State 11 were 40 to 74 percent. These State ratios by 

meal type were used to develop a national estimate of the number of meals that would have 

been reimbursed at Tier I rates for misclassified Tier I FDCHs. 

Exhibit 2.2: Share of Tier I Meal Types at Tier II FDCHs by State 

State Tier I Breakfasts Tier I Lunches/Dinners Tier I Snacks 

1 12% 20% 16% 

2 19% 25% 20% 

3 10% 16% 12% 

4 16% 17% 18% 

5 31% 30% 38% 

6 16% 17% 18% 

7 11% 9% 9% 

8 16% 18% 17% 

9 8% 7% 8% 

10 22% 21% 23% 

11 40% 72% 74% 

12 28% 22% 26% 

13 17% 16% 16% 

14 19% 39% 33% 

National Estimate 15% 16% 16% 

Source: 2006 CACFP Tiering Assessment. Table contains weighted estimates based on sponsor files for 930 Tier II FDCHS. 

Percentages by State are for descriptive purposes only because State-level samples are too small to produce robust State-level 

estimates. 
18

Annual Estimates of Under- and Over-Payments because of Misclassifications

The choice of using FDCHs that were reimbursed in a single month (September 2006) had 

consequences for how the annual costs associated with misclassified FDCHs were estimated. 

Ideally, the sample would have been drawn from all FDCHs that were active at any point from 

October 2005 through September 2006.20 That was not feasible and instead, the sample was 

drawn only from FDCHs that had reimbursable meals in September 2006. By using only 

FDCHs active in September, FDCHs that did not have reimbursable meals in September but 

had been active in some of the prior 11 months (October 2005 through August 2006) were 

missed. To compensate for this loss, FDCHs that were active in September were treated as if 

they were open all 12 months of the year. For many FDCHs, this was not true because they 

had been part of the program for less than 12 months or because they had no reimbursements 

for at least 1 month of the year. Consequently, the meals that were added to the FDCHs for 

which the FDCHs had actually not been reimbursed are assumed to offset the meals that were 

missed from FDCHs that were active at some point in the previous 12 months but not active in 

September.21 

Last year, another problem was that 17 sponsors did not provide meal counts for all 12 months. 

This year, there was only one sponsor that did not provide all 12 months of meal counts. This 

sponsor provided 11 months. To account for this, an “adjusted” yearly total of meals was 

created by type of meal and level of reimbursement (Tier I or Tier II). This was done by taking 

an average monthly meal count by type of meal and level of reimbursement, based on the 

number of months during which the FDCH had reimbursed meals, and multiplying by 12. 

Before finding the average monthly meal count, a seasonality factor (based on the national total 

meals served by type and by month; see data in Appendix Table A1.2) was calculated for each 

month the FDCH had reimbursed meals. This was to avoid any bias associated with specific 

months in which the FDCHs were open. Therefore, the average monthly figures were first 

seasonally adjusted by month before they were combined into yearly totals. 

Similar to income guidelines, reimbursement rates are made on an annual basis, and are also 

based on the period from July 1 through June 30. Because of a time shift in the study start 

date, this year’s data collection period covered two different reimbursement rate periods, from 

July 1, 2005 through June 30, 2006, and July 1, 2006 through June 30, 2007. The same 

method used for applying income guidelines was used, applying 75 percent of the rates from the 

period July 1, 2005 through June 30, 2006, and 25 percent of the rates from the period 

July 1, 2006 through June 30, 2007. This method was only necessary to calculate the cost of 

Lunch and Dinner Meals, as they were the only rates that increased from the previous year.22 

 

20 It should be noted that this year’s data collection an analysis window was slightly different from the initial year’s 

study, where the study year was June 2004 to May 2005. This year’s study spanned the 12 months from October 

2005 to September 2006. The shift in the study year was primarily due to the contractual start date for the study 

option, which was delayed. 

21 This approach results in an unbiased annual estimate of the number of meals served. However, because the 

sample could not be drawn from all homes that had been active at some point from October 2005 through September 

2006, the variance of the final estimates was higher. 

22 This weighting method does not have an effect on the amount of under- and over-under payments, as the 

difference between Tier I and Tier II reimbursement rates does not change from year to year, although the rate itself 

does increase. However, the weighting method does affect total expenditures for Tier I and Tier II. 
19

At this point, the total under- and over-payments resulting from tiering misclassification were 

computed. For Tier I FDCHs that were not validly classified, the cost for each FDCH was 

determined by the sum of equations 2.2 to 2.4, presented on the following page. 

(2.2) Breakfast loss = 12 * AvgMonthlyBrks * (1 - BRSHAREState) * (1.06 - .39) 

 where... 

 BRSHAREState = the share of breakfasts in Tier II FDCHs in that State 

 that were reimbursed at Tier I rates 

AvgMonthlyBrks = the average number of breakfasts served by the FDCH in a month 

(1.06 - .39) = the difference between Tier I and Tier II payments 

(2.3) Snack loss = 12 * AvgMonthlySnks * (1 - SNSHAREState) * (.58 - .16) 

 where... 

 SNSHAREState = the share of snacks in Tier II FDCHs in that State 

 that were reimbursed at Tier I rates 

AvgMonthlySnks = the average number of snacks served by the FDCH in 

a month 

 (.58 - .16) = the difference between Tier I and Tier II payments 

(2.4) Lunch/Supper loss = 12 * AvgMonthlyLDs * (1 - LNSHAREState) 

* [.75 * (1.96 - 1.18) + .25 * (1.97 - 1.19)] 

 where... 

 LNSHAREState = share of lunches and suppers in Tier II FDCHs in that 

 State that were reimbursed at Tier I rates 

AvgMonthlyLDs = the average number of lunches and suppers served by the FDCH in a month 

.75 * (1.96 - 1.18) + .25 * (1.97 - 1.19) = the difference between Tier I and Tier II payments 

To obtain an estimate of the monies not paid to Tier II FDCHs that were misclassified, a similar 

strategy of getting monthly totals was followed. Because the share of children who were 

already being reimbursed at Tier I rates was known, no State-based estimates were needed. 

The national estimates of monies under- and over-compensated at Tier I and Tier II FDCHs was 

simply the total of each misclassified FDCH multiplied by its respective weight. 
20

Estimating Upper and Lower Bounds of the Misclassification Rate

In a complex survey design as used in this study, the calculation of the variances of the 

estimates is likewise complex. The Taylor expansion method was used to estimate sampling 

errors of estimators.23 This method obtains a linear approximation for the estimator and then 

uses the variance estimate for this approximation to estimate the variance of the estimate. 

For a multistage sample design, the variance estimation method depends only on the first stage 

of the sample design. Therefore, the required input includes only first-stage cluster or primary 

sampling units (PSUs) and first-stage stratum identification. There is no need to input design 

information about any additional stages of sampling. This variance estimation method assumes 

that the first-stage sampling fraction is small or that the first-stage sample is drawn with 

replacement. If the sampling rate varies (unequal probability sampling), as in this study, one 

can create strata that approximate a uniform sampling rate. 

The PSUs (clusters) in the study were the States. However, one State (California) was a 

certainty and one (Minnesota) was a near-certainty. In these two States, each sponsor became 

a PSU. In Minnesota, one of the sponsors was large and was sampled four times. For 

Minnesota, the large sponsor was divided into four PSUs and two of the smaller ones were 

combined. 

The clusters were then paired up into "strata." The strata were designed so that clusters in the 

same strata were of the same kind (State or sponsor), in the same State (for sponsors) and with 

similar probabilities of selection. As in the previous study, there were 32 clusters and 16 strata 

in this year’s sample. The average probability of selection of the two clusters in a stratum were 

entered as the sampling rate of the stratum. This pairing of clusters is common in many 

variance estimation procedures, particularly when one needs to use a finite population 

correction. 

The first estimate was the proportion of misclassifications, obtained for the total population and 

the Tier I and Tier II domains separately. The estimate was obtained by adding the weights of 

the FDCHs incorrectly classified and dividing them by the sum of the weights. 

The second estimate was the total dollars associated with meals in validated misclassified 

FDCHs (174 Tier I FDCHs and 2 Tier II FDCHs). In this case, the average was first obtained 

and then was multiplied by the reported total number of FDCHs (see Appendix Table A1.1). In 

this way, the variance of the estimates of the total number of FDCHs in the program did not 

have to enter into the variance. 

The variance estimates have their own error of estimate. As a result, when calculating the 

confidence intervals, one must take into account the variance of the variance estimates. In 

order to do this, one must first obtain the degrees of freedom (the number of clusters minus the 

number of strata) and multiply the standard error by the t value for the 90% confidence interval 

for the degrees of freedom in question. 

 

23 The SAS procedure SURVEYMEANS was used. For further explanation of the statistical qualities of this approach, 

see: http://www.pop.upenn.edu/cores/computing/sasdoc/sashtml/stat/chap11/sect3.htm. 
21

CHAPTER 3. THE DATA COLLECTION PROCESS 

The data collected for this study was abstracted from sponsor files on site in a highly organized 

operation. Trained field data collectors abstracted the files containing documentation to support 

the tiering determination from sampled sponsors and FDCHs, and meal count information was 

collected for a 12-month period (October 2005 to September 2006). This discussion outlines 

the processes used to collect the study data. 

OVERVIEW OF THE DATA COLLECTION INSTRUMENT USED FOR THE STUDY 

The data collection instrument used for the 2006 study was developed, pre-tested, and used in 

the Base year (2005). That instrument, known as the Tiering Determination Instrument, was 

developed using algorithms that were created for validating a tiering determination based on the 

tiering method used (these algorithms were discussed in the previous chapter). The data 

collection instrument did not include the algorithms used for validating the determination: these 

algorithms were applied separately after the initial field data collection efforts. The Tiering 

Determination Instrument was a paper form created to collect the essential data elements 

needed to verify sponsors’ tiering designations. The instrument was used for Tier I and Tier II 

FDCHs, with the objective of recording all of the available information. The 2006 instrument 

was slightly modified from the previous version used in the 2005 study. The limited changes 

included updating the meal count portion of the instrument to reflect the current study’s duration, 

and minor adjustments to enhance readability and to clarify instructions to data collectors. In 

addition to collecting information on tiering, information on the number of meals reimbursed by 

tier type (Tier II FDCHs can have the meals of individual children who are income-eligible 

reimbursed at Tier I rates), meal type, and month during the period from October 2005 to 

September 2006 was recorded on the form.24 The data collection instrument can be found in 

Appendix 3. 

Training of the Data Collectors

A comprehensive training was developed for the 16 experienced field data collectors recruited 

for this study. All but two of the field data collectors had participated in the study in the Base 

year, and all of the field data collectors had experience in the field on other national studies. In 

addition to reviewing the sampling design and intricacies of the data collection instrument, the 

training also developed two additional methods for data collectors to use to ensure the sponsor 

identified all of the relevant documentation on site.25 The first method was an exit interview 

 

24 Most sponsors only had information on the number of meals for which they claimed reimbursement and not the 

number of children served per month. During the day, FDCHs can serve up to six food courses: breakfast, morning 

snack, lunch, afternoon snack, dinner, and evening snack. For each individual child, FDCHs can be reimbursed for a 

maximum of 2.5 meals (where a snack counts as a half of a meal). Consequently, during each day, different children 

receive different reimbursable meals and snacks, and one cannot determine the total number of children served 

during the day from just counts of meals claimed for reimbursement. This problem is obviously complicated even 

further when only monthly meal counts are available, as the same children need not be served all of the days that the 

FDCH is open. Therefore, there is no method to translate monthly meal counts to a total number of children for 

whom meal reimbursement claims are made that month. 

25 In the 2005 study, the validation effort determined that sponsors sometimes did not have all of the documents for a 

FDCH in one folder, especially in the case of the school boundary map. To account for this occurrence, this year’s 

procedures were developed to assist the sponsor in identifying all possible locations of information used in the tiering 

determination of the sampled FDCHs once on site. Sponsors did not know the identity of the sampled FDCHs before 

the data collector arrived on site. This procedure minimized the possibility that a sponsor would alter the FDCH files 

in any way before the data abstraction. 
22

protocol, which the data collectors used to ask the sponsor final questions about the 

organization and location of the FDCH files. The second method was a Sponsor Verification 

Form, which asked the sponsor to indicate by their signature that all of the relevant 

documentation for the sampled FDCHs had been identified and made available for copying by 

the data collector. The objective of both strategies was to prompt the sponsor into reviewing 

their files to identify any additional information that may have been stored separately from the 

FDCH file, but used in making the most recent tiering determination. 

To prepare for the field data collection, each of the data collectors participated in a 2-day 

training held in the Washington, DC area on November 30 and December 1, 2006. The training 

provided a comprehensive background on the program, understanding of the methods used to 

make a tiering determination, and hands-on review of and practice with documentation that was 

likely to be found on site in sample files. The purpose was for the data collector to gain 

familiarity with the actual types of documents that would be encountered in the field and from 

which data would be abstracted. Five mock files were created, and there were separate 

practice sessions filling out the collection instrument for each of the mock cases. 

During the training, each data collector was provided with a field data manual to obtain a solid 

background in the purpose and procedures of the project, to be effective at interacting with staff 

at sponsoring organizations when reviewing and abstracting data from files, and to 

communicate effectively with supervisory staff at Macro headquarters. The data collectors 

referred to the manual when questions arose in the field, and, if necessary, they were instructed 

to call Macro to address any unforeseen issues during a site visit. 

Arranging for Site Visits

The process of arranging for the actual onsite data abstraction began with efforts in creating the 

sample (described further in Appendix 2). After the States for the sample were selected, FNS 

Regional Offices contacted State representatives. Then Macro contacted States (first by mail, 

then by phone) to explain the purpose of the project, enlist their support, and determine whether 

there were any unique features in how the CACFP operated in their State. The first task was to 

get the requisite information to pull the sponsor sample for each State, including the number of 

sponsors and the number of FDCHs for each sponsor. Macro called the selected States to 

identify whether there were any unique features of the program that would affect the data 

collection. In one State, the State office was responsible for determining Tier I area eligibility on 

the basis of Census and elementary school eligibility.26

Once the sponsors were selected, they were sent a letter of introduction that explained the 

purpose of the study. A follow-up phone call was made to ask questions about where sponsor 

tiering determination documents were kept. Because sponsors organize their files in different 

ways, data collectors asked detailed questions about accessing the files. Data collectors 

completed a detailed telephone interview to abstract as much information as possible about the 

organization and location files, as well as the availability of meal count data over the October 

2005 to September 2006 timeframe. By asking multiple questions about file locations, enough 

information was obtained to ensure that the data collectors would be able to complete the data 

collection instrument accurately. The exact date of each site visit was established by the data 

 

26 As in the Base year (2005) the State office overseeing the program in one of the sampled States had responsibility 

for making all tiering determinations. 
23

collectors, who called the relevant sponsor contact to establish a mutually convenient time for 

the visit. 

Collecting Data at Sponsor Administrative Sites

When the data collectors arrived at the sponsor locations, they presented the sponsor’s 

representative with the list of FDCHs that were to be abstracted. This was the first time the 

sponsors were provided with the list of FDCHs to be studied. A couple of sponsors had asked 

to see the list before arrival, so they could have the relevant files ready when the data collectors 

arrived. Though this seemed to be a good faith effort to be cooperative, the sponsors’ request 

were refused to avoid the possibility of them altering the data for the FDCHs. 

Once at the site, most of the data collectors were left alone to complete the abstraction. In one 

State, a State representative accompanied the data collector on each of the site visits. This 

occurred in the previous study, and did not seem to have a negative impact on the data 

collection. The State representative helped the data collector to number pages and photocopy 

documents. From time to time, sponsor representatives also checked on the data collectors to 

ensure that everything was going smoothly. These contacts did not affect the data collection. 

The central part of the data collection was filling out the Tiering Determination Instrument and 

photocopying all relevant documents in each FDCH’s records, beginning with the meal counts. 

This information was collected first because each data collector needed to verify that the 

sampled FDCHs had received reimbursements in September 2006. If the meal count records 

indicated that some of the sampled FDCHs did not have meal reimbursements in September, 

the FDCH was dropped. The data collector used the ordered list of replacement FDCHs to 

replace the FDCH that was not in scope. 

In last year’s sample, 22 of the 95 sponsors surveyed did not have meal counts for the previous 

12 months available because they had been archived at a storage facility offsite, with 

8 sponsors having fewer than 9 months of meal counts. As shown in Appendix Table A1.3, all 

but one of the sponsors had 12 months of meal counts in this year’s study. The remaining 

sponsor had 11 months of meal counts. 

The remaining data collection tasks involved the identification of appropriate documentation in 

each file. In most cases, there was at least a single sheet of paper indicating the provider’s 

name, when the FDCH was open, and what tier the FDCH was assigned. In all Tier I files and 

some Tier II files, it was critical to identify any documentation attempting to demonstrate 

eligibility for Tier I status. Documentation of Tier II FDCHs was collected to determine whether 

any of these FDCHs were eligible for Tier I status. Because Tier II is the default status, no 

documentation is needed. Consequently, the vast majority of Tier II FDCHs had no documents 

in their folders other than the sponsor statement indicating that the FDCH was a Tier II FDCH. 

However, any indication that Tier I status was applied for was abstracted for the FDCH. If there 

was information showing that an FDCH tried to qualify for Tier I status in more than one manner, 

all of the data were collected and evaluated. 

Data collectors completed the remaining portions of the tiering determination instrument and 

copied the appropriate documents, all of which where transmitted in an individually labeled file 

for each case to Macro for final review. The data collection event concluded with the exit 

interview and completion of the Sponsor Verification Form. Trained project staff reviewed these 

files and made the final determination as to whether the FDCH was correctly classified while 

editing the file. 
24

Creating the Data Analysis File

After the data collection instruments were returned, they were checked for completeness and 

legibility. Recorded meal counts were carefully reviewed, as was the supporting documentation 

for each case. These edited data collection instruments were double-key entered with a 

100 percent accuracy check. 

After all of the instruments had been transferred to an electronic format, a thorough review of 

the data elements was conducted to verify meal counts, check for missing data elements, and 

verify that all listed elementary schools met the standard of at least half of its students being 

eligible for free and reduced-price meals (when adequate documentation for this was missing 

from the file). Tiering classifications were carefully evaluated for correctness. Because of the 

complexity of the income eligibility process (there were often many different sources of income 

from different family members), every FDCH in which income data were entered was rechecked 

to ensure that all of the fields were correctly edited and entered. 

Data Validation Procedures

The outcomes of the data validation procedures are presented in Chapter 4, but this discussion 

highlights the steps taken in applying the validation algorithms to cases identified as being 

misclassified in the initial analysis. Once the analytic data set was created, a computer analysis 

program was developed to determine which FDCHs were improperly classified and what the 

reason was for the deficiency. Although these cases were technically deficient, it was likely that 

most of these FDCHs were indeed Tier I eligible, based on outcomes of a similar process in the 

2005 study. To confirm the status of these procedural errors, a series of follow-up validation 

operations were undertaken for each type of error in a sequential fashion. 

The procedural errors that occurred in cases attempting to use school boundary area as the 

basis for Tier I status were verified by using the validation algorithm described in Chapter 2. 

When the documentation did not support a clear FDCH-elementary school link, the Mapquest 

feature was used to identify the nearest elementary school, which was then tentatively chosen 

as the elementary school serving these FDCHs. This was only a preliminary allocation that was 

verified by follow-up phone calls. Once all the FDCHs had a school identified, the telephone 

numbers of the schools were obtained from the National Center for Educational Statistics 

Website27 or other Web-based sources. Each of the schools was called to verify that the 

address of the FDCH was served by that school. In most cases, the person answering the 

phone (often an administrative assistant or secretary) was able to give a definitive response. If 

not, other school representatives were contacted until a definitive answer was obtained. 

 

27 http://nces.ed.gov/ccd/schoolsearch/. 
25

When school representatives said that the FDCH was not in their attendance area, they were 

asked for a suggestion of the proper school for this address. In most cases, an alternative 

school was given. When no alternative option was given, Mapquest was used to identify the 

next most likely school. This school was then contacted to verify that they served the address 

of the FDCH. This process was repeated until a definitive positive answer was received. Once 

a new school was identified, the State lists of eligible elementary schools having at least 

50 percent of the students eligible to receive a free or reduced price meal were used to confirm 

that the correct school was on the list. If the school was not on the list, then the FDCH was 

considered as misclassified. The Census block group method was then used to determine if 

these misclassified cases should remain misclassified and receive the lower tiering status. The 

Census Fairdata CACFP mapper tool was used for follow up with these cases. In cases where 

the Census method indicated the FDCH qualified for Tier I status, that status was maintained by 

the case. In all other cases, the FDCH remained misclassified. 

For those cases that attempted to use the Census block group method as the basis for the initial 

tiering determination, procedural errors were followed up on by first using the information in the 

existing file to conduct the Census lookup independently. In cases where the Census method 

did not validate the Tier I status, the follow-up then moved to use the existing data to identify an 

elementary school for the FDCH and continued with the established procedure for identifying 

and verifying an FDCH-elementary link and the eligibility of the elementary school. In cases 

where there was no information allowing for a school match, or in cases where the school 

boundary method resulted in the lower tiering status, the case remained misclassified. 

For cases where the procedural errors were related to the provider income method, the existing 

documentation was first reviewed to determine if an elementary school could be identified for 

the FDCH. If so, this information was used to attempt the school boundary method tiering 

determination. For the remaining cases where no school was identified, research was 

conducted using Mapquest to identify a possible elementary school, and then calls were made 

to confirm the link between the FDCH and the elementary school in question. In cases where 

the calls indicated that the FDCH-school link did not exist, the Census method was used to 

validate the tiering determination. In cases where the school was not on the State list of 

qualifying schools, the Census method was also employed to validate the tiering determination. 

Out of these cases, those for which the Census method confirmed the lower tiering status 

retained the misclassification designation. 

For those FDCHs where the documentation did not support a Tier I determination based on 

categorical eligibility, the documentation was reviewed to determine whether there was any 

evidence to support investigation by Census. The FDCH address was used in the Census 

Fairdata CACFP mapping tool, and the results were then used to confirm or deny the Tier I 

status of the FDCH. In cases where the Census method did not confirm the original Tier I 

determination, an attempt to qualify the FDCH based on the school boundary method was 

made. The Census method was attempted in these cases first because the available evidence 

in files where categorical eligibility is used often did not contain any identifying information 

outside of the FDCH address. For cases where the school boundary method was determined to 

not be viable, the case remained misclassified. 
26

CHAPTER 4. RESULTS OF DATA COLLECTION, 

VALIDATION, AND ANALYSIS 

This chapter presents the outcomes of the data collection, follow-up validation, and analysis, 

beginning with a summary of the analysis findings prior to the data validation efforts. An 

overview of those FDCHs classified as Tier I and meal reimbursements by tier is presented first, 

and then misclassification rates based on reviews of documentation in sponsor files during the 

initial data collection period. Outcomes of the analysis of procedural misclassifications are then 

presented, followed by the revised misclassification rates and their associated costs. 

In this section, all percentages shown are weighted and derived from the study sample. Actual 

numbers of FDCHs cited are unweighted. As expected in a sample that uses probabilities 

proportional to size, the weighted percentages are often very close to those that would have 

been obtained from unweighted data. 

TIER I SHARE OF FDCHS AND MEAL REIMBURSEMENTS 

This discussion begins with a summary of the analysis of data based on the initial data 

collection activities. On the basis of the sampling and weighting procedures of this data 

collection prior to the follow-up validation activities, 71 percent of FDCHs were classified as 

Tier I by their sponsors (see Exhibit 4.1) during the 12-month study period.28 The findings 

reflect considerable variation across sponsors and States on the share of Tier I FDCHs. As 

Exhibit 4.1 indicates, at the State level, three States had more than 90 percent of their FDCHs 

classified as Tier I, while four States had fewer than 60 percent of its FDCHs designated as Tier 

I. At the sponsor level, 12 sponsors classified all of their FDCHs as Tier I, while 17 sponsors 

classified 50 percent or less of their FDCHs as Tier I (see Appendix Table A1.4). 

 

28 Of the 3,150 FDCHs surveyed, 2,220 were classified as Tier I. 
27

Exhibit 4.1: Share of FDCHs Classified as Tier I by their Sponsors by State, 

Before Data Validation 

State Tier I Share 

11 100% 

5 92% 

12 90% 

10 86% 

3 77% 

2 75% 

6 70% 

13 60% 

4 63% 

1 63% 

7 59% 

8 54% 

14 52% 

9 42% 

National Estimate 71% 

Source: 2006 CACFP Program Assessment. Based on sponsor files for 3,150 FDCHs. Percentages by State are for descriptive 

purposes only because State-level samples are too small to produce robust State-level estimates. 

Another way to look at the use of program resources is by the share of expenditures for Tier I 

reimbursed meals and snacks. This figure is greater than the share of Tier I FDCHs for two 

reasons. First, since Tier I meals are reimbursed at much higher rates, the monetary share of 

Tier I reimbursed meals was higher than the share of FDCHs. Second, at Tier II FDCHs, many 

meals and snacks (15 to 16 percent nationally) were reimbursed at Tier I rates because of the 

income status of individual children. Consequently, the national estimate from this study 

concludes that 77 percent of the meals and snacks, and 87 percent of expenditures were for 

Tier I reimbursed meals and snacks (see Exhibit 4.2) during the study period. 

Exhibit 4.2: Meals and Expenditures Reimbursed at Tier I and Tier II Rates 

Number of Meals 

and Snacks Expenditures 

Share of Meals 

and Snacks 

Share of 

Expenditures 

 Tier I 477,872,447 $586,774,703 77% 87% 

 Tier II 144,753,831 $84,989,626 23% 13% 

 Total 622,626,278 $671,764,329 100% 100% 

Source: 2006 CACFP Tiering Assessment. National, weighted, seasonally adjusted estimates based on sponsor files for 

3,150 FDCHs. 

The most common way in which FDCHs were qualified by their sponsors for Tier I status was 

through area eligibility using the local elementary school (74.7 percent), followed by provider 

income (14.5 percent), area eligibility using Census (6.7 percent), and income eligibility by 

categorical documents (1.3 percent). Approximately 3 percent of FDCH records included at 

least partial documentation for two or three different approaches (Exhibit 4.3). 
28

Exhibit 4.3: Basis of Tier I Qualification and Procedural Misclassification Rates— 

Original Data Collection Sponsor Files 

Documentation 

Type 

Percentage of 

Documentation* 

Procedural 

Misclassification 

Rate

Weighted National 

Estimates of Tier I FDCHs 

School 74.7% 27.6% 21,288 

Income 14.5% 33.7% 5,076 

Census 6.7% 6.9% 475 

Categorical 1.3% 52.8% 608 

Multiple Types of 

Documentation 

2.8% 29.3% 881 

*The percentage of documentation sums to more than 100% because of rounding. Source: 2006 CACFP Tiering Assessment. 

Based on sponsor files for 2,220 Tier I FDCHs (unweighted). 

Initial analysis also produced a misclassification rate for the tiering status of FDCHs. After all 

the data were extracted from sponsor records of the sampled FDCHs, the tiering algorithms 

were applied to determine whether the available documentation supported the listed tiering 

status assigned by sponsor. The lack of supporting documentation or ambiguous 

documentation was deemed a procedural error and flagged for follow-up verification in the 

validation data collection, as described in Chapter 3. Of the 2,220 Tier I FDCHs, sponsors did 

not have adequate supporting documentation of this status for 632 FDCHs. Of the 930 Tier II 

FDCHs, 2 had documents in the file showing that they were eligible for Tier I status. In 

percentage terms, the weighted procedural misclassification rates were 27.5 and 0.22 percent 

for Tier I and Tier II FDCHs, respectively. For the Nation as a whole, the overall estimated 

procedural misclassification rate was 19.5 percent. 

Exhibit 4.3 also displays the procedural misclassification rate by type of approach used to 

qualify for Tier I status. For sponsors using multiple types of documentation, an FDCH was 

considered procedurally misclassified if the documentation in the file did not support Tier I 

classification regardless of which approach might have been used.29 The highest rate of 

procedural error (52.8 percent) occurred when sponsors used categorical eligibility as the basis 

for the tiering determination. The error rate for cases based on categorical eligibility was 

highest due to the small number of cases on which the error rate is based. This meant that 

every case that was in error represented a larger proportion of all cases involving categorical 

eligibility.30 For each additional home that is in error, the error rate will increase substantially. 

As the exhibit illustrates, while the procedural error rate for the school boundary method is 27.6 

 

29 It is worth emphasizing that the FDCH was considered procedurally and not substantively misclassified. In 

2.8 percent of cases, sponsors attempted to qualify FDCHs for Tier I status using two or three criteria. The 

procedural misclassification rate relates the percentage of times that the use of a specific criterion—without regard to 

the number of criteria they may have attempted—failed to support the claim for Tier I status. Thus, when a sponsor 

attempted to use the characteristics of the local elementary school solely, they failed to document the school’s 

eligibility almost 28 percent of the time. However, in the majority of such cases, further investigation led to the 

conclusion that the FDCH was indeed qualified for Tier I status even though sponsor documentation was inadequate. 

For about 3 percent of the FDCH records examined, sponsors attempted to use multiple approaches. In about 

29 percent of these instances, none of the approaches supported the sponsor’s classification of Tier I. 30 Note that the sample was designed to produce reliable national estimates, not estimates by type of sponsor 

classification method. The small number of homes classified by this method does not adversely affect the national 

estimates of error. This discussion is for descriptive, not estimation, purposes. 
29

percent, the largest percentage of FDCHs (75 percent) were classified through this approach.31

Hence, the vast majority of procedural errors involved linking an FDCH with an eligible school. 

The large proportion of procedural errors associated with the school boundary method is similar 

to the 2005 study findings. 

Exhibit 4.4 provides additional information on the specific types of errors found in the FDCH 

files. In about 20 percent of these potential errors, there was no map or official school map 

(e.g., a Mapquest map). In about 46 percent of the cases, there was an official map but it was 

either undated (23 percent) or not valid (22.5 percent) because the date preceded the 3-year 

qualification window for tiering determinations. There were also many FDCHs in which the 

income statement of the provider did not adequately meet the requirements of the program. 

The most common problem was the verification of self-declared financial information. This was 

resolved in some cases, when legitimate documentation on both income and expenses was 

present in the file. Otherwise, it was not possible to accept self-declared information. Other 

documentation errors included incomplete income eligibility forms (not properly signed, dated, or 

not including the provider’s Social Security Number), failure to date or document a source of 

income, or total income being above the threshold set for the household size. 

 

31 As Exhibit 4.3 indicates, 75 percent of FDCHs attempting to qualify for Tier I status attempted to do so on the basis 

of the local elementary school only. However, including the 3 percent that took multiple approaches, some involved 

the use of local elementary school demographics, raising the overall rate to 77 percent. 
30

Exhibit 4.4: Causes of Tier I Procedural Misclassifications 

Causes of 

Misclassification Percentage 

Weighted National 

Estimates of Tier I 

FDCHs with Procedural 

Misclassifications 

SCHOOL BOUNDARY METHOD 

No Date on Map 23.0% 6,548 

Expired Date on Map 22.5% 6,387 

Inappropriate or Missing Map 19.8% 5,623 

School Not Eligible 8.7% 2,482 

PROVIDER INCOME METHOD 

Missing Element on Income Eligibility Application 6.6% 1,885 

Unacceptable Ledger Sheet 5.2% 1,484 

No Date or Initial on Memo 4.6% 1,315 

Excess Income 4.5% 1,279 

No Documentation for Income Source 2.3% 647 

CATEGORICAL ELIGIBILITY METHOD 

Categorical 1.8% 524 

CENSUS BLOCK GROUP METHOD 

Census 0.9% 245 

Total 100.0% 28,419 

Source: 2006 CACFP Assessment. Weighted estimates based on sponsor files for 2,220 Tier I FDCHs. 

In this year’s study, 11 sponsors with at least half of their FDCHs classified as Tier I had 

procedural misclassification rates above 50 percent. Conversely, 9 sponsors with at least 

50 percent of their FDCHs classified as Tier I did not have a single error relating to classification 

in their files (see Appendix Table A1.4). 

As for Tier II FDCHs, the two FDCHs in error did have documentation in the file showing that the 

home was Tier I qualified on the basis of income. There was proper documentation of Tier I 

status, but the wrong tiering level had been assigned by the sponsor. 

RESULTS OF THE INDEPENDENT TWO-STAGE VALIDATION APPROACH OF 

TIERING DETERMINATIONS WITH PROCEDURAL MISCLASSIFICATIONS 

As described earlier, independent verification of the FDCH’s tiering level was conducted when 

the documentation in the sponsor’s file was found to be insufficient or inconclusive. In contrast 

to the 2005 study where only those cases with errors related to the school boundary method 

were investigated, the 2006 study included the review of procedural errors in the Census block 

group, as well as categorical and income eligibility methods. It was not within the scope of the 

study to review any other documentation other than what was present in the FDCH sponsor file. 

Follow-up for FDCHs with procedural errors was limited to using the existing documentation to 

determine if the Tier I status could be supported by using either the school boundary method, 

the primary validation method, or the Census block group method, the secondary validation 

method. As described in Chapter 3, the Census block group method was only attempted in 
31

cases where the school boundary method resulted in either an inconclusive or lower tiering 

status determination.32 

In the following discussion, the results of the primary independent verification of Tier I status 

using the school boundary method are presented first, including the impact of the verified 

FDCHs on the estimates of the costs of misclassification. The report then presents the results 

of the secondary verification using the Census block group method and incorporates these 

findings in the final analysis. 

Exhibit 4.5 presents an overview of the initial procedural misclassifications for each of the four 

tiering determination methods. Of the total 632 Tier I FDCHs with a procedural 

misclassification, 489 were the result of poor documentation in the school boundary method. 

Of these cases, 430 lacked documentation clearly linking a specific elementary school to the 

FDCH’s address, while for 57 cases, the supporting documents in their files were too weak to 

definitively link that school to the FDCH. Two cases had no supporting documentation at all. 

The high number of cases with procedural errors related to the school boundary method is very 

similar to the number of cases with this error in the 200533 study (641 FDCHs with unsupported 

tiering status in 2005; 632 in 2006; 488 were the result of poor school boundary documentation 

in 2005, 489 in 2006). The next largest number of procedural misclassifications (113) occurred 

with documentation used to support provider income as the basis for the tiering determination.34

 

32 It should be noted that the school boundary method was attempted first in the independent verification procedures 

for all tiering methods except for when the original tiering status was determined using the Census block group 

method. In this instance, the original method was first attempted independently and then the school boundary 

method was attempted. This ordering is outlined in the algorithms presented in Chapter 3. 33 Child and Adult Care Food Program (CACFP): Assessment of Sponsor Tiering Determinations, 2005 Final Report. 34 For sponsors attempting multiple methods of tiering determination and failing at each attempt, the case was 

classified as an error based on a hierarchy of determination methods using FRP eligibility as a guideline for 

prioritizing the listing (school, Census, categorical, and then income) and then assigned the error code according to 

whatever means was the first to be attempted in this listing. For example, if a sponsor tried to qualify based on 

school and Census, and failed at each, the error is classified as an error in the school method. If a sponsor used 

Census and income and failed at both, the error was classified as a Census error. 
32

Exhibit 4.5: Procedural Misclassification and Documentation Failure: 

Identifying Cases for Verification Follow-up 

Documentation of Tier I Status Failure 

Unweighted 

Count of 

Sampled 

Tier I FDCHs 

Collected Data Shows FDCH Does Not Link to the School 430 

A Specific, Qualified School Could Not Be Identified from Documentation 57 

No Documentation Supporting School Method 2 

School Boundary Errors 489 

Ledger Sheet Errors 31 

No Documentation 13 

Other Income Errors 69 

Provider Income Documentation 113 

Categorical Eligibility Documents Missing Dates, Signatures or Expired 17 

Categorical Eligibility Errors 17 

No Documentation of Census Method Outcome 13 

Census Block Group Method Errors 13 

Follow-up Conducted to Verify Procedural Misclassifications 632 

Total Tier I Procedural Misclassifications (unweighted) 632 

PROCEDURES USED TO VERIFY THE ELIGIBILITY OF FDCHS WITH 

PROCEDURAL MISCLASSIFICATIONS 

As described in Chapter 3, each tiering method had a distinct algorithm for determining tiering 

status. The procedures used for the validation data collection are described in detail for each 

tiering method used in the following discussion. Exhibit 4.6 presents a flowchart depicting the 

procedures used for validating the errors associated with each tiering determination method. It 

presents the results of the primary validation of procedural errors (using the school boundary 

method) to independently determine the tiering status of the FDCH. The flowchart then 

presents findings where the Tier I status could not be supported by the school boundary method 

and the Census block group method was attempted. 
33

Exhibit 4.6: Total Number of FDCHs with Unsupported Documentation—Procedural Misclassificati

Confirmed as Tier I through the Primary and Secondary Validation Procedures 
34

Primary Validation of Procedural Misclassifications in the Original Tiering 

Method: Using the School Boundary Method to Verify Tier I Status 

Primary Validation of Procedural Misclassifications: School Boundary 

The analysis identified 489 cases where the school boundary method was used and 

documentation was inconclusive in determining the tiering status of the FDCH. Of these, 

430 FDCHs did not have documentation supporting the FDCH-school link, 2 had no 

documentation supporting either the FDCH link or school eligibility criteria, and 57 FDCHs 

lacked supporting documentation that the school met the FRP guidelines. 

The primary validation of these procedural misclassifications began by examining the 430 cases 

where the files lacked documentation clearly linking a specific elementary school to the FDCH’s 

address, or the supporting documents in the files were too weak to definitively link that school to 

the FDCH. The first step in this process was to verify that the FDCH address did link to a 

qualifying elementary school for these cases. Where the documentation was weak, Mapquest 

was used to identify a possible elementary school that served the FDCH. The National Center 

of Education Statistics Website (http://nces.ed.gov/globallocator/) was used to identify telephone 

numbers for these schools, and they were contacted by phone to verify that the FDCH address 

was within the school catchment area for the elementary school. For the 430 cases with this 

error, the verification procedures confirmed that the school attendance area included the 

specific FDCH in question. 

Once the FDCH-school link was confirmed, the validation activities continued by referring to the 

State lists of qualifying elementary schools to ensure that the school in question did indeed 

meet the criteria of having at least 50 percent of its students eligible for a free or reduced-price 

meal. All 430 of the FDCHs examined at this stage were found to meet this criterion. 

A separate examination of the 57 FDCHs where the documentation indicated that the school 

was ineligible was then conducted. These cases required investigation of the State school lists 

to confirm the elementary school eligibility as well. Of these 57 cases, 24 FDCHs were 

confirmed as being linked to the school attendance area and linked to an eligible school. 

A separate investigation was conducted for the two cases with no documentation. Mapquest 

was used to identify a school; the school was contacted to verify the link. The next step was to 

check the State lists of eligible schools. The outcome of this research was that both of the two 

FDCHs were linked to a school that was eligible. At this stage of the validation process, 

456 FDCHs were confirmed as being Tier I, while additional attempts using the school boundary 

method were unsuccessful for the remaining 33 FDCHs. Notably, the validation procedures 

reduced the school boundary method misclassification rate from 27.6 to 2.1 percent (see 

Exhibit 4.7). 

Primary Validation of Procedural Misclassifications: Provider Income 

There were a considerable number of FDCHs (113) where the documentation did not support 

Tier I status based on provider income. The validation data collection began with attempts to 

validate the Tier I status of these FDCHs using the school boundary method. A review of the 

existing files was conducted to determine if an elementary school could be identified for the 

FDCH. Research was conducted using Mapquest to identify a possible elementary school for a 

majority of the FDCHs. After the elementary school and the telephone number were identified, 
35

verification telephone calls to schools were made to confirm that the elementary school 

attendance area did include the FDCH. When the school representative indicated that the 

FDCH was not in their service area, the representative was asked for a likely suggestion, and 

that alternate school was contacted. 

Once the FDCH-school link was confirmed, the State lists were also consulted to confirm school 

eligibility. Of the 113 FDCHs with procedural misclassifications for provider income, 49 were 

confirmed as having both the FDCH-school link and an eligible school. The remaining 64 

FDCHs were linked to elementary schools that were not eligible, based on State lists. The 

primary validation procedures had a more limited effect on the misclassification rate in this 

instance, as the provider income misclassification rate changed from 33.7 to 18.6 percent (see 

Exhibit 4.7). 

Primary Validation of Procedural Misclassifications: Categorical Eligibility 

The validation of the 17 FDCHs where documentation did not support Tier I status based on 

categorical eligibility began with an examination of FDCH files for information to conduct an 

independent school boundary determination. Mapquest was used to identify an elementary 

school located near the FDCH address, and the National Center for Educational Statistics 

Website was used to identify contact numbers for these schools. The telephone verification 

procedure identified 15 FDCHs as having the necessary FDCH-school link. When the State 

eligibility lists were checked against these 15 FDCHs, 2 of them were affiliated with schools that 

were not eligible based on the free and reduced-price meal criterion. At this stage in the 

validation follow-up, 13 of the 17 FDCHs were confirmed in their Tier I status using the school 

boundary method. The remaining 4 FDCHs could not be confirmed using the school boundary 

method. Thus, validation procedures reduced the categorical method misclassification rate from 

52.8 to 13.4 percent (see Exhibit 4.7). 

Primary Validation of Procedural Misclassifications: Census Method 

The validation of the 13 FDCHs where documentation did not support Tier I status began with 

an examination of the FDCH files for information on conducting an independent Census block 

group method determination. FDCH address information was present in the files of all 13 

cases, and this information was used with the Fairdata Web-based tool. Through this method, 9 

of the 13 FDCHs were confirmed to be Tier I eligible. In this case, the validation procedures 

reduced the Census method misclassification rate from 6.9 to 2.3 percent (see Exhibit 4.7). 

Exhibit 4.7: Primary Verified Misclassification Rates by Tiering Method 

Documentation 

Type 

Percentage of 

Documentation 

Procedural 

Misclassification 

Rate 

Primary Verified 

Misclassification 

Rate 

Verified 

Weighted 

National 

Estimates of 

Tier I FDCHs

School 74.7% 27.6% 2.1% 1,635 

Income 14.5% 33.7% 18.6% 2,798 

Census 6.7% 6.9% 2.3% 158 

Categorical 1.3% 52.8% 13.4% 173 

Multiple Types of 

Documentation 2.8% 29.3% 4.8% 136 
36

The end result of these data validation procedures was that out of the 632 FDCHs with 

procedural misclassifications, 527 FDCHs retained their Tier I status based on the outcomes of 

the primary validation efforts (see Exhibit 4.6). 

Results after Incorporating the Primary Independent Verification of Procedural 

Misclassification

The primary independent verification procedures resulted in confirmed Tier I status for 527 of 

the 632 surveyed FDCHs with procedural misclassifications. Using these findings, the national 

estimate of the misclassification rate was then determined to be 4.78 percent for Tier I FDCHs 

(see Exhibit 4.8), compared with the 27.5 percent of FDCHs (procedurally weighted) for which 

documentation in sponsor files was missing or inadequate in the first round. The Tier II 

misclassification rate was not subject to further investigation and remained at 0.22 percent. The 

overall misclassification rate fell to 3.44 percent from 19.49 percent by incorporating the results 

of the primary verification procedures. Also included in Exhibit 4.8 are estimates for the upper 

and lower bounds of these estimates. Exhibit 4.9 presents the unweighted counts of both 

procedural and verified errors. 

Exhibit 4.8: Primary Verified Misclassification Rates by Tiering Status 

Type of 

FDCH 

Primary Verified 

Misclassification 

Rate 

Lower Limit* Upper Limit* 

Weighted 

National 

Estimates of 

FDCHs*** 

Tier I 4.78% 3.46% 6.10% 103,408 

Tier II 0.22% 0.08% 0.36% 42,884 

All Tier I or Tier II FDCHs 3.44% 2.65% 4.23% 146,292 

* 90 percent confidence level. ***Total homes estimated from sample. Source: 2006 CACFP Tiering Assessment. Based on 

sponsor files for 3,150 FDCHs and follow-up verification (weighted estimates). 

Exhibit 4.9: Comparison of Procedural to Primary Verified Errors for Sampled FDCHs 

Type of Home Procedural Error Primary Verified Error 

Yes No Yes No 

Tier I 632 1,588 105 2,115 

Tier II 2 928 2 928 

All Sampled Tier I or Tier II FDCHs 634 2,516 107 3,043 

Source: 2006 CACFP Tiering Assessment. Based on sponsor files for 3,150 FDCHs including follow-up for 489 Tier I FDCHs with 

procedural misclassifications based upon local elementary school. 
37

Exhibit 4.10 presents the causes of the primary verified errors for the 105 Tier 1 FDCHs for 

which the validation data collecting activities confirmed that the Tier I status was unsupported. 

Exhibit 4.10: Causes of Primary Verified Misclassification for Tier I FDCHs 

Causes of 

Misclassification Percentage 

Weighted 

National 

Estimates of 

Misclassified 

Tier I FDCHs 

Unacceptable Ledger Sheet 18.6% 921 

Excess Income 18.0% 889 

Inappropriate or Missing Map 15.2% 753 

No Date on Map 12.5% 620 

Missing Element on Income Eligibility Application 11.1% 550 

No Documentation for Income Source 8.9% 438 

School Not Eligible* 6.2% 305 

Categorical 3.5% 173 

Census 3.2% 158 

Multiple Forms of Documentation** 2.8% 136 

Expired Date on Map 0.0% 0 

No Date or Initial on Memo 0.0% 0 

Total 100.0% 4,943 

* All FDCHs without any documentation are assumed to have been Tier I on the basis of area eligibility by elementary school. 

** Some FDCHs had documents in their files that supported different approaches for Tier I eligibility. Source: 2006 CACFP Tiering 

Assessment. Based on sponsor files for 2,220 Tier I FDCHs and follow-up verification (weighted estimates are provided). 
38

Of the 92 sponsors in the sample, 45 did not have a single Tier I misclassification after the 

primary validation procedures were completed. Another 33 sponsors had a misclassification 

rate of less than 10 percent, including 13 sponsors with a misclassification rate of 5 percent or 

less. Of the remaining 14 sponsors, 2 had a misclassification rate of over 30 percent (see 

Appendix Table A1.4). At the State level, 2 States had misclassification rates over 10 percent. 

At the other extreme, one State had no misclassifications (see Exhibit 4.11). 

Exhibit 4.11: Primary Verified Tier I Misclassification Rate by State 

State Verified Tier I Misclassification Rate 

9 19.0% 

14 13.0% 

7 7.0% 

5 6.7% 

4 5.8% 

10 5.5% 

1 5.2% 

2 4.9% 

8 4.5% 

13 3.8% 

12 2.0% 

6 2.0% 

3 1.2% 

11 0.0% 

National Estimate 4.78% 

Source: 2006 CACFP Tiering Assessment. Based on sponsor files for 2,220 Tier I FDCHs and verification follow-up. Percentages 

by State are for descriptive purposes only because State-level samples are too small to produce robust State-level estimates. 

Costs of Misclassifications after the Primary Validation of Procedural Errors

Using the procedures discussed in Chapter 2, the annual cost of improper payments35

associated with misclassified FDCHs for this study was calculated incorporating the findings 

from the primary validation efforts. The annual cost of improper payments36 associated with 

misclassified FDCHs is estimated to be $11.4 million, with a 90 percent confidence range of 

between $8.4 and $14.4 million (see Exhibit 4.13), which includes the findings from the primary 

independent tiering verification process. Exhibit 4.12 presents a comparison of estimated costs 

of improper payments for all FDCHs in 2005 and 2006 after the primary validation procedures. 

As the chart depicts, the overall estimated costs of misclassifications decreased in 2006 by 

about $1.6 million dollars. 

 

35 That is, the sum of the overpayments to Tier I homes and the absolute value of the underpayments to Tier II 

homes. 

36 That is, the sum of the overpayments to Tier I homes and the absolute value of the underpayments to Tier II 

homes. 
39

Exhibit 4.12: Comparison of Estimated Costs of Improper Payments 

for All FDCHs, 2005 and 2006, After Primary Verification of Procedural Errors* ** 

All FDCHs (Improper Payments)

$9.4

$13

$16.6

$8.4 

$14.4 

$11.4

$0

$5,000,000

$10,000,000

$15,000,000

$20,000,000

Lower Bound Estimated Cost Upper Bound

Millions

CACFP 2005 CACFP 2006

* 2005 and 2006 CACFP Tiering Assessment. Chart depicts rounded data. **90 percent confidence level. 

The greater part of these overpayments are due to misclassified Tier I FDCHs, estimated to be 

$11.2 million, with a confidence range between $8.3 and $14.2 million based on the verification 

of errors using the school boundary method. Overpayments to Tier I FDCHs represent 

2.0 percent of the estimated expenditures for meal reimbursements for Tier I FDCHs 

($560,405,65137). This ratio is less than the misclassification rate of Tier I FDCHs (4.78 

percent) because only part of the cost of the meal—the difference between Tier I and Tier II 

reimbursement rates—translates into an overpayment. More specifically, meals at misclassified 

Tier I FDCHs would be reimbursed at approximately half the rate of Tier I reimbursed meals 

(especially when accounting for the fact that about 16 percent of Tier II FDCH meals are 

reimbursed at the higher Tier I rate). 

 

37 The total amount of meal reimbursements for Tier I FDCHs (after subtracting out the estimated reimbursements for 

children who qualify for Tier I rates, regardless of their FDCHs' classifications) that could potentially be classified as 

erroneous over-payments or costs. 
40

Exhibit 4.13: Costs of Misclassifications after Primary Verification Procedures 

Estimated 

Cost 

Cost as 

% of 

Total 

Reimbursements Lower 

Bound 

Estimate*

Lower 

Bound 

as % 

of 

Total 

Upper 

Bound 

Estimate* 

Upper 

Boun

d as 

% of 

Total 

Weighted 

National 

Estimates 

of 

FDCHs **

* 

Tier I FDCHS 

(Overpayment) 

$11,249,292 2.00% $8,301,852 1.64% $14,196,731 2.80% 103,408 

Tier II FDCHs 

(Underpayment) 

 $146,852 0.13% $77,938 0.07% $215,765 0.19% 42,884 

All FDCHs 

(Improper 

Payments) 

$11,396.144 1.7% $8,441,351 1.37% $14,350,936 2.32% 146,292 

* 90 percent confidence level. *** Based on the sample. Source: 2006 CACFP Tiering Assessment. National estimates based on 

sponsor files for 3,150 FDCHs and verification follow-up. Weighted figures are presented. 

For Tier II FDCHs, the amount of underpayments was estimated to be $146,852, which 

represents less than 1 percent of the total funding for meals for Tier II FDCHs (an estimated 

$111,358,67938). Combining the absolute value of the estimated cost of Tier I and Tier II 

misclassifications leads to a total amount of under- and over-spending of $11,396,144 which 

represents approximately 1.7 percent of total spending for all Tier I and II FDCHs. 

Exhibit 4.14 shows the number of meals provided to FDCHs by their listed tiering level and the 

number of meals reimbursed at the wrong rate after the primary verification of errors. For Tier I 

FDCHs, 18.3 million of the 459.7 million meals reimbursed were reimbursed at the wrong rate. 

For Tier II homes, 227,423 out of 162.9 million meals served were reimbursed at the wrong rate. 

 

38 The total amount of meal reimbursements for Tier II FDCHs (after taking under consideration the estimated 

reimbursements for children who qualify for Tier I rates, regardless of their FDCHs' classifications) that could 

potentially be classified as erroneous under-payments or costs. 
41

Exhibit 4.14: Annual Number of Meals Served and Number of 

Meals Reimbursed at Incorrect Rate by FDCH Tier Type, 

after Primary Verification Procedures 

Breakfasts 

Lunches and 

Suppers Snacks 

Total Meals 

and Snacks 

Tier I FDCHs 

Total 112,500,623 176,541,213 170,658,448 459,700,284 

Reimbursed at Wrong Rate* 5,355,922 6,138,669 6,839,560 18,334,221 

Tier II FDCHs 

Total 44,115,045 58,286,729 60,524,219 162,925,993 

Reimbursed at Wrong Rate 28,636 122,709 76,078 227,423 

Source: 2006 CACFP Tiering Assessment. Figures based upon seasonally adjusted monthly averages within States. *The 

calculation of meals at Tier I FDCHs reimbursed at the wrong rate takes into account the fact that, with a change in tiering status, 

not all meals would be reimbursed at Tier II rates. The adjustment is made by deducting State proportions of Tier I meals served in 

Tier II homes. For Tier II FDCHs, only meals reimbursed at Tier II rates are subject to error. Eighteen of the Tier I FDCHs in the 

sample that were incorrectly classified claimed some Tier II meals. These Tier II meals were not included in the estimate of meals 

reimbursed at the wrong rate, but are included in the total meals for Tier I FDCHs. 

Secondary Validation of Remaining Procedural Misclassifications in the Original 

Tiering Method: Using the Census Block Group Method to Verify Tier I Status 

Overall, 105 of the 632 FDCHs remained in error after the primary validation phase had 

concluded. As outlined in Chapter 3, the next phase of the verification of procedural errors 

called for the use of the Census block group method to be applied to any remaining FDCHs 

where the original tiering status could not be verified. This discussion presents the results of the 

Census block group independent verification of Tier I status for those errors that were not 

resolved using the school boundary method. 

Secondary Validation of Procedural Misclassifications: School Boundary

The primary validation follow-up had resulted in 456 of the 489 cases with procedural errors 

being confirmed as valid Tier I FDCHs, leaving 33 FDCHs that could not be verified using this 

method. The Census block group method was used to try to validate the tiering status of these 

33 remaining procedural misclassifications. The Census block group method investigation used 

the Census Fairdata CACFP mapper tool (http://www.fairdata2000.com/CACFP/) to identify 

whether the FDCH had an address in a Census track where at least 50 percent or more of the 

children under age 13 lived in households at or below 185 percent of the poverty level. The 

FDCH address for each of these 33 cases was entered into the tool. A Census block map, 

indicating percentages of the students under age 13 living in households at or below the poverty 

level, was then generated. This procedure was followed for each of the 33 FDCHs, resulting in 

an additional 12 FDCHs confirmed as Tier I using the Census method. The remaining 21 

procedural misclassifications could not be validated as Tier I by the Census method either, and 

these cases retained their misclassification designation. The secondary validation procedures 

reduced the school boundary misclassification rate further, from 2.1 percent after the primary 

validation efforts to 1.5 percent (see Exhibit 4.15). 
42

Secondary Validation of Procedural Misclassifications: Provider Income

Of the 113 procedural errors with the provider income method, 64 cases were not able to be 

independently confirmed as Tier I using the school boundary method. The Census method was 

then used to attempt to validate the tiering status of these 64 remaining cases. Once again, the 

Fairdata tool was used, and only 5 FDCHs were confirmed as having Tier I status using this 

method. The remaining 59 FDCHs remained misclassified. The secondary validation 

procedures had a more limited effect on the misclassification rate in this instance, as the 

provider income misclassification rate changed from 18.6 percent to 17.1 percent (see 

Exhibit 4.15). 

Secondary Validation of Procedural Misclassifications: Categorical Eligibility

The validation of the 17 FDCHs where documentation did not support Tier I status confirmed 13 

of these 17 cases as Tier I through the school boundary method, leaving 4 cases that needed 

follow-up using the Census block group method. When the Census method was attempted, 

none of these 4 FDCHs could be confirmed as having Tier I status and thus remained 

misclassified. The secondary validation procedures did not have any effect on the categorical 

method misclassification rate, as it remained at 13.4 percent (see Exhibit 4.15). 

Secondary Validation of Procedural Misclassifications: Census Method

As stated earlier, the validation protocol required that in cases where it was possible, the 

original tiering determination method should be independently attempted to resolve the 

procedural error. This meant that in the case of FDCHs that were determined to be Tier I using 

the Census approach, the primary verification method was an independent attempt at the 

Census method. Nine of the 13 procedural errors associated with this method were confirmed 

as Tier I under the primary verification process, leaving 4 remaining cases as procedural errors. 

The school boundary method was attempted for the remaining 4 FDCHs. As the files contained 

no information identifying a local elementary school, Mapquest was used to first identify possible 

elementary schools that served the FDCHs. Once schools were identified, the National Center 

for Educational Statistics Website was used to identify contact numbers, and follow-up 

verification phone calls were made to determine whether these FDCHs were indeed served by 

elementary schools in which at least 50 percent of the students are eligible for a free or 

reduced-price meal. For all 4 FDCHs, the FDCH-school link was confirmed, but the elementary 

school was not on the State list of eligible schools. These 4 FDCHs remained misclassified. 

The secondary validation procedures did not alter the Census method misclassification rate, as 

it remained at 2.3 percent (see Exhibit 4.15). 
43

Exhibit 4.15: Misclassification Rates by Tiering Method, Secondary 

Verification Procedures 

Documentation Type 

Percentage 

of Documentation 

Procedural 

Misclassification Rate 

Primary 

Verification 

Misclassification Rate 

Secondary 

Verification 

Misclassification Rate 

Verified 

Weighted 

National 

Estimates 

of 

Tier I 

FDCHs 

School 74.7% 27.6% 2.1% 1.5% 1,130 

Income 14.5% 33.7% 18.6% 17.1% 2,573 

Census 6.7% 6.9% 2.3% 2.3% 158 

Categorical 1.3% 52.8% 13.4% 13.4% 173 

Multiple Types 

of 

Documentation 

2.8% 29.3% 4.8% 4.8% 136 

RESULTS AFTER INCORPORATING THE SECONDARY INDEPENDENT 

VERIFICATION OF PROCEDURAL MISCLASSIFICATIONS 

The secondary independent verification procedures resulted in confirmed Tier I status for an 

additional 17 cases, resulting in a total of 544 FDCHs confirmed as Tier I through the verification 

procedures of the 632 surveyed FDCHs with procedural misclassifications. Overall, 88 of the 

cases with procedural errors remained in error. Using these findings, the national estimate of 

the misclassification rate was then determined to be 4.03 percent for Tier I FDCHs (see Exhibit 

4.16). Once again, the Tier II misclassification rate was not subject to further investigation and 

remained at 0.22 percent. Using the findings from the secondary verification procedures, the 

overall misclassification rate fell to 2.92 percent from 3.44 percent. Exhibit 4.17 presents the 

unweighted counts of both procedural and verified errors, for both the primary and secondary 

validation procedures. 

Exhibit 4.16: Secondary Verified Misclassification Rates by Tiering Status 

Type of 

FDCH 

Verified 

Misclassification 

Rate 

Lower 

Limit* 

Upper 

Limit* 

Weighted 

National 

Estimates of 

FDCHs*** 

Tier I 4.03% 2.76% 5.31% 103,408 

Tier II 0.22% 0.08% 0.36% 42,884 

All Tier I or Tier II FDCHs 2.92% 2.14% 3.69% 146,292 

* 90 percent confidence level. ***Total homes estimated from sample. Source: 2006 CACFP Tiering Assessment. Based on 

sponsor files for 3,150 FDCHs and follow-up verification (weighted estimates). 
44

Exhibit 4.17: Comparison of Procedural to Verified Errors for Sampled FDCHs, 

Primary and Secondary Validation Procedures 

Procedural Error Primary Verified Error Secondary Verified Error 

Type of Home Yes No Yes No Yes No 

Tier I 

632 1,588 105 2,115 88 2,132 

Tier II 

2 928 2 928 2 928 

All Sampled Tier I 

or Tier II FDCHs 634 2,516 107 3,043 90 3,060 

Source: 2006 CACFP Tiering Assessment. Based on sponsor files for 3,150 FDCHs including follow-up for 489 Tier I FDCHs with 

procedural misclassifications based upon local elementary school. 

Overall, the secondary validation process resulted in a reduction of the misclassification rate for 

11 sponsors. Of the 92 sponsors in the sample, an additional 5 sponsors, for a total of 50, were 

found to not have any misclassification errors after the secondary validation procedures were 

completed. The secondary validation process increases to 15 the number of sponsors in the 

sample with a misclassification rate of less than 5 percent. Only 1 of the 92 sponsors had a 

misclassification rate over 30 percent after the secondary validation process (see Appendix 

Table A1.4). At the State level, the secondary validation procedures resulted in modest 

decreases in the misclassification rate within States, and reduced the national misclassification 

rate from 4.78 percent to 4.03 percent (see Exhibit 4.18). 

Exhibit 4.18: Verified Tier I Misclassification Rate by State 

State 

Primary Verification Tier I 

Misclassification Rate 

Secondary Verification Tier I 

Misclassification Rate 

9 19.0% 17.8% 

14 13.0% 12.0% 

7 7.0% 7.0% 

5 6.7% 6.2% 

4 5.8% 4.3% 

10 5.5% 4.3% 

13 5.2% 3.8% 

1 4.9% 3.7% 

2 4.5% 3.7% 

8 3.8% 2.7% 

6 2.0% 1.3% 

3 2.0% 1.2% 

12 1.2% 1.0% 

11 0.0% 0.0% 

National Estimate 4.78% 4.03% 

Source: 2006 CACFP Tiering Assessment. Based on sponsor files for 2,220 Tier I FDCHs and verification follow-up. Percentages 

by State are for descriptive purposes only because State-level samples are too small to produce robust State-level estimates. 
45

COSTS OF MISCLASSIFICATIONS AFTER THE SECONDARY VERIFICATION 

OF PROCEDURAL ERRORS 

The next step in the analysis was to include the findings from the secondary validation 

procedures into those calculations developed for determining the annual cost of improper 

payments. Using this data, the annual cost of improper payments39 associated with 

misclassified FDCHs for this study is estimated to be approximately $9.4 million, with a 90 

percent confidence range of between $6.5 and $12.2 million (see Exhibit 4.20), which includes 

the findings from both the primary and secondary independent tiering validation processes. 

Using this data, the overall estimated costs of misclassifications have decreased in 2006 by 

approximately $3.6 million dollars (Exhibit 4.19). 

Exhibit 4.19: Comparison of Estimated Costs of Improper Payments 

for All FDCHs, 2005 and 2006* ** 

All FDCHs (Improper Payments)

$9.4

$13

$16.6

$6.5 

$12.2 

$9.4

$0

$5,000,000

$10,000,000

$15,000,000

$20,000,000

Lower Bound Estimated Cost Upper Bound

Millions

CACFP 2005 CACFP 2006

* 2005 and 2006 CACFP Tiering Assessment. Chart depicts rounded data. **90 percent confidence level. 

When examining the findings, the majority of improper payments are the result of overpayments 

to misclassified Tier I FDCHs, estimated to be $9.2 million, with a confidence range between 

approximately $6.5 and $12 million. Using the findings from both the primary and secondary 

verification of procedural errors, overpayments to Tier I FDCHs represent 1.64 percent of the 

estimated expenditures for meal reimbursements for Tier I FDCHs ($560,405,65140). Once 

again, this ratio is less than the misclassification rate of Tier I FDCHs (4.03 percent) because 

only part of the cost of the meal—the difference between Tier I and Tier II reimbursement 

rates—translates into an overpayment. 

 

39 That is, the sum of the overpayments to Tier I homes and the absolute value of the underpayments to Tier II 

homes. 

40 The total amount of meal reimbursements for Tier I FDCHs (after subtracting out the estimated reimbursements for 

children who qualify for Tier I rates, regardless of their FDCHs' classifications) that could potentially be classified as 

erroneous over-payments or costs. 
46

Exhibit 4.20: Costs of Misclassifications 

Estimated Cost 

Cost as 

% of 

Total 

Reimburs

ements 

Lower 

Bound 

Estimate* 

Lower 

Bound 

as % 

of 

Total 

Upper 

Bound 

Estimate* 

Upper 

Boun

d as 

% of 

Total 

Weighted 

National 

Estimates 

of FDCHs 

*** 

Tier I FDCHs 

(Overpayment) $9,206, 139 1.64% $6,407,469 1.14% $12,004,810 2.14% 103,408 

Tier II FDCHs 

(Underpayment) $146,852 0.13% $77,938 0.07% $215,765 0.19% 42,884 

All FDCHs 

(Improper 

Payments) $9,352, 991 1.39% $6,547,135 0.97% $12,158,847 1.81% 146,292 

* 90 percent confidence level. *** Based on the sample. Source: 2006 CACFP Tiering Assessment. National estimates based on 

sponsor files for 3,150 FDCHs and verification follow-up. Weighted figures are presented. 

For Tier II FDCHs, the amount of estimated underpayments remained unchanged after the 

secondary verification efforts. This amount, $146,852, still represents less than 1 percent of the 

total funding for meals for Tier II FDCHs (an estimated $111,358,67941). Combining the 

absolute value of the estimated cost of Tier I and Tier II misclassifications leads to a total 

amount of under- and over-spending of $9,352,991, which represents approximately 1.4 percent 

of total spending for all Tier I and II FDCHs. 

Exhibit 4.21 incorporates the findings from the secondary validation process, showing the 

number of meals provided to FDCHs by their listed tiering level and the number of meals 

reimbursed at the wrong rate. For Tier I FDCHs, 15 million of the 459.7 million meals 

reimbursed were reimbursed at the wrong rate, and for Tier II homes, 227,423 out of 

162.9 million meals served were reimbursed at the wrong rate. 

 

41 The total amount of meal reimbursements for Tier II FDCHs (after taking under consideration the estimated 

reimbursements for children who qualify for Tier I rates, regardless of their FDCH`s' classifications) that could 

potentially be classified as erroneous under-payments or costs. 
47

Exhibit 4.21: Annual Number of Meals Served and Number of 

Meals Reimbursed at Incorrect Rate by FDCH Tier Type 

Breakfasts 

Lunches and 

Suppers Snacks 

Total Meals 

and Snacks 

Tier I FDCHs 

Total 112,500,623 176,541,213 170,658,448 459,700,284 

Reimbursed at Wrong Rate* - 

Primary Verification 5,355,922 6,138,669 6,839,560 18,334,221 

Reimbursed at Wrong Rate* - 

Secondary Verification 4,425,949 4,987,253 5,596,895 15,010,097 

Tier II FDCHs 

Total 44,115,045 58,286,729 60,524,219 162,925,993 

Reimbursed at Wrong Rate 28,636 122,709 76,078 227,423 

Source: 2006 CACFP Tiering Assessment. Figures based upon seasonally adjusted monthly averages within States. 

*The calculation of meals at Tier I FDCHs reimbursed at the wrong rate takes into account the fact that, with a change in tiering 

status, not all meals would be reimbursed at Tier II rates. The adjustment is made by deducting State proportions of Tier I meals 

served in Tier II homes. For Tier II FDCHs, only meals reimbursed at Tier II rates are subject to error. Eighteen of the Tier I FDCHs 

in the sample that were incorrectly classified claimed some Tier II meals. These Tier II meals were not included in the estimate of 

meals reimbursed at the wrong rate, but are included in the total meals for Tier I FDCHs. 
48

CHAPTER 5. CONCLUSION 

The study findings indicate that the most common way in which FDCHs were qualified by their 

sponsors for Tier I status was through area eligibility using the local elementary school 

(74.7 percent), followed by income of the provider (14.5 percent), area eligibility using Census 

(6.7 percent), and income eligibility by categorical documents (1.3 percent). Records for about 

3 percent of sampled FDCHs included at least partial documentation for two or three different 

approaches. These findings are similar to those of the 2005 study. 

The national estimate from this study found that 77 percent of the meals and snacks, and 

87 percent of expenditures, were for Tier I reimbursed meals (see Exhibit 4.2) during the study 

period. Procedural errors in tiering determinations, if left unchecked, have a significant negative 

impact on improper payments. The initial review of the information collected from sponsor files 

for 3,150 FDCHs yielded weighted procedural misclassification rates of 27.5 percent and 

0.22 percent for Tier I and Tier II FDCHs, respectively, resulting in an overall misclassification 

rate of 19.5 percent. After independently verifying the tiering status of 632 Tier I FDCHs with a 

procedural misclassification, the misclassification rate declined to 3.44 after the primary 

verification of these errors, and to 2.92 percent overall after the secondary verification efforts. 

Even after attempts to establish Tier I status through approaches not used by the sponsor, there 

were some notable procedural misclassifications associated with the provider income method. 

A review of the errors associated with this method of determining tier status suggests that 

sponsors may have difficulty explaining the provider income guidelines to FDCH providers. 

Several sponsors seemed unaware of the provisions that disallowed negative business income 

and, in most cases, supporting receipts or pay stubs were missing from the files. While 

procedural errors associated with provider income were not validated in the 2005 study, a 

review of the documentation indicated that many of the errors were caused by the same 

mistakes in documenting the tiering determination. 

While provider income errors were an issue, the largest proportion of procedural errors were still 

related to attempts at qualifying an FDCH using the school boundary method, a finding that is 

similar to the outcomes of last year’s study. As was the case in the 2005 study, a majority of the 

procedural errors in the 2006 study (489) were related to issues in documenting the FDCHschool link. Errors in adequate documentation of maps connecting the address of an FDCH to a 

specific elementary school, maps that were out of date, and maps missing dates and official 

initials were identified in the initial analysis (Exhibit 4.4). The rules are clear: only an official 

school boundary map can be used, the map must be dated, and the date must be current or a 

note must be present indicating that a map with an old date is still applicable. If maps are not 

available, telephone calls to schools are permitted as long as there is an initialed and dated 

memo in the file indicating the name of person who verified that the school served the FDCH 

address. Based on the analysis, some sponsors do not maintain proper documentation to 

correctly link a FDCH to a qualifying elementary school, even though the validation efforts often 

result in a confirmation of the Tier I status. 

Sponsors failed to adequately document the tiering status of 2.92 percent of all Tier 1 or Tier II 

FDCHs after secondary verification efforts. The lower and upper bounds of this rate were 2.14 

and 3.69 percent, respectively (Exhibit 4.16). In terms of dollars for either overpayments on Tier 

I reimbursements or underpayments on Tier II reimbursements, the total amount of improper 

payments is estimated at approximately $9.4 million, with a lower bound of $6.5 million and an 

upper bound of $12.2 million. Overall, in the 2005 study, the combined over and under 

payments to misclassified FDCHs were estimated to be about $13 million, with a 90 percent 
49

confidence range of between $9.4 and $16.6 million. The difference in the total improper 

payments of $9.4 million in 2006 and $13 million in 2005 may be attributable to the two stage 

validation approach that was developed to check procedural errors for all Tier I FDCHs. 

The two stage validation approach, (which consisted of primary verification using the school 

boundary method to independently document the Tier I status of FDCHs with procedural errors, 

and secondary verification using the Census block group method) resulted in the ability to 

support the Tier I status for a large number of procedural errors. The two stage validation 

approach had a limited impact on some types of procedural errors (errors with documentation 

that relied on the categorical or provider income tiering determination methods), but did result in 

a sizeable reduction of procedural errors in the school boundary method, reducing the 

procedural error in this tiering method from 27.6 percent to 1.5 percent. The two stage 

approach also resulted in 50 of the 92 sponsors (54 percent) in the sample having no Tier I 

misclassifications after the validation process. 
Appendix 1. 

Tables 
A-1 

Table A1.1: Sample of States 

State FDCHs Sampled 

AK 491 0 

AL 1,304 0 

AR 890 0 

AZ 3,650 0 

CA 19,536 2 

CO 2,094 0 

CT 929 0 

DE 869 0 

FL 2,412 1 

GA 3,378 0 

HI 321 0 

IA 2,241 0 

ID 382 0 

IL 7,725 1 

IN 1,751 0 

KS 4,160 1 

KY 714 0 

LA 5,488 1 

MA 5,057 1 

MD 3,667 0 

ME 1,277 0 

MI 6,664 0 

MN 9,679 1 

MO 1,694 0 

MS 528 0 

MT 875 0 

NC 3,501 0 

ND 1,413 1 

NE 2,721 0 

NH+VT 730 0 

NJ 700 0 

NM 5,818 0 

NV 254 0 

NY 8,191 1 

OH 3,411 0 

OK 2,944 0 

OR 2,655 0 

PA 2,119 0 

RI 417 0 

SC 780 0 

SD 652 0 

TN 1,558 1 

TX 7,011 1 

UT 1,975 0 

VA+DC 2,518 1 

WA 3,477 1 

WI 3,605 1 

WV 1,617 0 

WY 448 0 
A-2 

Table A1.2: Monthly Adjustments for Seasonality 

Breakfasts Snacks Lunch/Dinners 

JANUARY 1.01 1.01 0.97 

FEBRUARY 0.96 0.95 0.91 

MARCH 1.11 1.11 1.07 

APRIL 0.96 0.96 0.95 

MAY 1.10 1.08 1.05 

JUNE 1.03 1.03 1.13 

JULY 0.87 0.90 1.02 

AUGUST 1.05 1.06 1.14 

SEPTEMBER 0.95 0.94 0.89 

OCTOBER 1.02 1.01 0.96 

NOVEMBER 0.98 0.98 0.94 

DECEMBER 0.95 0.96 0.97 
A-3 

Table A1.3: Maximum Months of Available Meal Counts 

Number of Months Number of Sponsors Percentage 

11 1 1.1 

12 91 98.9 
A-4 

Table A1.4: Sponsor Tier I Classifications and Misclassification Rates 

Tier I Misclassification Rates 

Sponsor 

Sampled 

FDCHs 

Share of 

FDCHs 

Sponsor 

Classified 

as Tier I 

Procedural 

Misclassification

Rate 

Primary Verified 

Misclassification

Rate 

Secondary 

Verified 

Misclassification

Rate 

93 31 87.1% 0.0% 0.0% 0.0% 

94 31 61.3% 26.3% 5.3% 0.0% 

101 31 96.8% 30.0% 3.3% 3.3% 

102 31 67.7% 33.3% 0.0% 0.0% 

103 31 77.4% 16.7% 0.0% 0.0% 

104 31 83.9% 76.9% 0.0% 0.0% 

105 31 64.5% 5.0% 5.0% 5.0% 

106 31 41.9% 23.1% 0.0% 0.0% 

107 31 80.6% 68.0% 8.0% 4.0% 

108 31 71.0% 31.8% 0.0% 0.0% 

109 31 80.6% 40.0% 0.0% 0.0% 

110 31 41.9% 92.3% 0.0% 0.0% 

111 31 87.1% 77.8% 3.7% 3.7% 

112 30 50.0% 46.7% 0.0% 0.0% 

113 31 87.1% 37.0% 3.7% 3.7% 

114 29 51.7% 80.0% 0.0% 0.0% 

115 15 100.0% 100.0% 0.0% 0.0% 

116 15 73.3% 45.5% 18.2% 18.2% 

117 28 64.3% 38.9% 0.0% 0.0% 

118 60 53.3% 28.1% 12.5% 12.5% 

119 31 41.9% 53.8% 7.7% 7.7% 

120 31 87.1% 22.2% 7.4% 7.4% 

121 31 38.7% 0.0% 0.0% 0.0% 

122 31 90.3% 25.0% 7.1% 7.1% 

123 31 100.0% 51.6% 6.5% 0.0% 

124 31 67.7% 33.3% 0.0% 0.0% 

125 31 90.3% 0.0% 0.0% 0.0% 

126 31 93.5% 34.5% 0.0% 0.0% 

127 31 93.5% 3.4% 0.0% 0.0% 

128 31 96.8% 0.0% 0.0% 0.0% 

129 31 74.2% 34.8% 0.0% 0.0% 

130 31 67.7% 19.0% 0.0% 0.0% 

131 62 59.7% 16.2% 0.0% 0.0% 

132 31 61.3% 5.3% 5.3% 5.3% 

133 61 57.4% 28.6% 17.1% 11.4% 

134 31 83.9% 26.9% 3.8% 3.8% 

135 31 16.1% 80.0% 20.0% 20.0% 

136 31 80.6% 12.0% 4.0% 0.0% 

137 31 67.7% 9.5% 4.8% 4.8% 

138 30 73.3% 13.6% 0.0% 0.0% 

139 31 83.9% 11.5% 3.8% 3.8% 

140 31 45.2% 21.4% 21.4% 14.3% 

141 31 100.0% 6.5% 0.0% 0.0% 

142 31 100.0% 3.2% 0.0% 0.0% 
A-5 

Tier I Misclassification Rates 

Sponsor 

Sampled 

FDCHs 

Share of 

FDCHs 

Sponsor 

Classified 

as Tier I 

Procedural 

Misclassification

Rate 

Primary Verified 

Misclassification

Rate 

Secondary 

Verified 

Misclassification

Rate 

143 31 96.8% 16.7% 0.0% 0.0% 

144 31 100.0% 0.0% 0.0% 0.0% 

145 63 100.0% 0.0% 0.0% 0.0% 

146 31 100.0% 48.4% 0.0% 0.0% 

147 31 83.9% 0.0% 0.0% 0.0% 

148 31 35.5% 0.0% 0.0% 0.0% 

149 30 40.0% 16.7% 8.3% 8.3% 

150 31 64.5% 25.0% 10.0% 0.0% 

151 91 46.2% 9.5% 4.8% 4.8% 

152 31 35.5% 36.4% 36.4% 36.4% 

153 31 29.0% 22.2% 0.0% 0.0% 

154 115 48.7% 32.1% 21.4% 19.6% 

155 24 33.3% 0.0% 0.0% 0.0% 

156 30 30.0% 11.1% 0.0% 0.0% 

157 93 57.0% 43.4% 13.2% 11.3% 

158 15 60.0% 44.4% 22.2% 22.2% 

159 15 93.3% 28.6% 7.1% 7.1% 

160 61 24.6% 53.3% 20.0% 20.0% 

161 31 45.2% 42.9% 7.1% 7.1% 

162 31 100.0% 45.2% 9.7% 3.2% 

163 30 70.0% 19.0% 9.5% 9.5% 

164 31 83.9% 26.9% 11.5% 11.5% 

166 60 100.0% 6.7% 1.7% 1.7% 

167 30 100.0% 20.0% 0.0% 0.0% 

168 23 87.0% 5.0% 0.0% 0.0% 

169 6 100.0% 0.0% 0.0% 0.0% 

170 30 100.0% 43.3% 3.3% 0.0% 

171 31 93.5% 0.0% 0.0% 0.0% 

172 27 92.6% 96.0% 20.0% 20.0% 

173 31 93.5% 93.1% 10.3% 10.3% 

174 31 83.9% 80.8% 7.7% 7.7% 

175 31 90.3% 10.7% 7.1% 7.1% 

176 31 80.6% 28.0% 4.0% 4.0% 

177 31 96.8% 3.3% 0.0% 0.0% 

178 31 58.1% 66.7% 0.0% 0.0% 

179 31 80.6% 12.0% 0.0% 0.0% 

180 31 74.2% 4.3% 4.3% 4.3% 

181 31 74.2% 21.7% 0.0% 0.0% 

182 31 67.7% 0.0% 0.0% 0.0% 

184 31 54.8% 5.9% 5.9% 5.9% 

185 31 67.7% 38.1% 23.8% 19.0% 

186 31 90.3% 7.1% 3.6% 3.6% 

187 31 64.5% 5.0% 0.0% 0.0% 

188 31 96.8% 13.3% 0.0% 0.0% 

189 31 51.6% 25.0% 6.3% 6.3% 

190 62 93.5% 96.6% 3.4% 3.4% 
A-6 

Tier I Misclassification Rates 

Sponsor 

Sampled 

FDCHs 

Share of 

FDCHs 

Sponsor 

Classified 

as Tier I 

Procedural 

Misclassification

Rate 

Primary Verified 

Misclassification

Rate 

Secondary 

Verified 

Misclassification

Rate 

191 31 48.4% 53.3% 6.7% 6.7% 

192 31 51.6% 12.5% 0.0% 0.0% 

Unweighted 

Total 

3,150 74.2% 27.4% 4.78% 4.03% 
Appendix 2. 

Assumptions in Sample Selection and 

Weighting Procedures
A-7 

APPENDIX 2: ASSUMPTIONS IN SAMPLE SELECTION AND 

WEIGHTING PROCEDURES 

SAMPLING DESIGN 

The sampling approach was designed to allow for the production of national point estimates of 

the number of misclassified FDCHs and a cost range, in terms of misallocated reimbursements, 

that could be associated with these erroneous tiering designations. The study required 90 

percent confidence in these estimates, plus or minus 2.5 percentage points. The Office of 

Research, Nutrition and Analysis (ORNA) requested that we develop a sampling strategy that 

assumes an error rate no greater than 25 percent in the assignment of tiering levels by sponsor, 

and that was based on a population of 160,000 FDCHs at the time the initial design was 

derived. To obtain a sample of the required power and precision for Year 1(2005 study), it was 

determined that the process would require the selection of 30 FDCHs for each of 7 sponsors 

within 15 States, for a total of 3,150 FDCHs. The standard errors obtained from such a sample 

were examined at the end of the study and were found acceptable for the objectives of the 

study. Even though some additional variables were examined, the sampling design for 2006 

was identical to that of the 2005 study. For the rationale for the sampling design, see the Year 1 

sampling plan (2005 CACFP Tiering Assessment). 

Again as in the 2005 study, FDCHs are clustered within sponsors, which in turn, are nested 

within individual States. To derive the equivalent of a random sample at an acceptable cost, we 

first selected the States.42 Then, within the selected States sponsors were selected. States 

were selected on the basis of probabilities proportionate to size (PPS) and the same was done 

for sponsors within selected States once contact information from the State agencies was 

provided. Once sponsors were selected, we obtained a list of homes from each sponsor, and 

we selected FDCHs for assessment and abstraction of files randomly. For (i) States and 

(ii) sponsors, the size measure was the number of FDCHs relative to (i) the number of FDCHs 

participating in the United States and (ii) the number of homes participating in the sponsors’ 

States. 

SELECTING STATES 

Because many other processes depended on an expedited selection of States, Macro 

accomplished that task based upon the most current data available from FNS at the beginning 

of the study in September 2006. As outlined above, the assumption of an error rate no greater 

than 25 percent in the assignment of tiering levels inferred an optimal sampling design that 

called for 30 homes to be sampled from each of the 7 sponsors in each of 15 States, for a total 

of 3,150 homes. To minimize the design effect through weighting, the design also needed to 

assign each home approximately the same probability of selection as every other home. This 

was done with the PPS sampling procedure described earlier, whereby our size measure was 

the number of FDCHs in each State. PPS Sampling may be done with replacement (where a 

sampled State always has a chance of being selected again), without replacement (where a 

State can only be sampled once) or with minimal replacement (where only States with sizes that 

exceed the sum of the sizes divided by the number to be sampled can be sampled more than 

once). Sampling with minimal replacement guarantees approximately the same probability of 

 

42 Territories such as Guam, Puerto Rico and the Virgin Islands were excluded; although the District of Columbia was 

included. 
A-8 

selection to every home while retaining a diversity of States. To implement this approach, we 

allowed for the possibility that States containing more than 1/15 of the total number of FDCHs 

might be sampled more than once. The calculation of the expectations of selection indicated 

that California was the only State that could be selected more than once in the study. 

Our process for drawing the sample of States began after receiving the list indicating the 

number of FDCHs in each State from FNS. Each State needed to have at least 210 FDCHs 

participating in the CACFP (7 sponsors x 30 FDCHs). If a State had fewer than 210 homes, its 

sponsors and FDCH were combined with those of a neighboring State. This was done twice, 

once combining New Hampshire and Vermont, and again combining the District of Columbia 

and Virginia. For each State—combined or singularly—the proportion of all the U.S. FDCHs 

found in that State were multiplied by the number of States to be sampled (15) to provide the 

expectation of selection for the State. If this expectation was less than 1, the expectation 

represented the probability that the State would be selected once. If it was greater than 1, the 

integer represented the number of times the State was to be selected with certainty, and the 

modulus (the fractional part less than 1) became the probability that the State would be selected 

an additional time. The sum of all expectations equaled 15. 

Once expectations were calculated, States were sorted by FNS region. Subsequently, and 

within region, they were resorted (“shuffled”) randomly. This procedure guaranteed proportional 

representation by region. With this approach, the number of States selected within each region 

was set within one,43 and each region was guaranteed to be represented by a minimum of one 

State. This last guarantee was not merely an artifact of the methodology, but was based on the 

fact that no region had less than 1/15 of the homes in the Nation. 

The following exhibit, using the latest FNS data, indicates the expected number of States to be 

selected for each region: 

Exhibit A2.1: The Expectation of the Number of Homes Selected per Region 

REGION HOMES EXPECTATION 

1 16,601 1.70 

2 11,491 1.18 

3 14,176 1.45 

4 32,835 3.37 

5 22,152 2.27 

6 18,273 1.87 

7 30,764 3.15 

Total 146,292 15.00 

 

43 That is, before the sample was drawn, the allocation of States per region could be determined within one. For 

example, if the expectation for a particular region (the sum of the expectations for the States within the region) was 

1.7, then we can know that at least one State in the region would be selected, and possibly two. Conversely, if the 

regional expectation was 0.7, then we could be sure that one State might be selected; but then again, it would be 

possible that zero State within the sample might be selected. Because the expectation for each region was never 

less than one, we could be certain—before selection—that at least one State in every region would be drawn. 
A-9 

The exhibit shows that, in Regions 1, 2, 3, and 6, at least one State be selected, and some 

chance of two States in a region. We knew with certainty that at least two States and, perhaps, 

three would represent Region 4. Similarly, Regions 4 and 7 would be represented by a 

minimum of three States. Note that the regional expectations sum to 15, the number of States 

required by the sampling plan. 

The next step in the process was to generate a random number between 0 and 1 and add it to 

the expectation of the first State in the ordering to form the first State’s cumulative expectation. 

For each subsequent State, the expectation for that particular State was added to the 

cumulative expectation of the previous State to form its cumulative expectation. The 

expectation for each State was equal to the number of FDCHs in the State, divided by the total 

number of FDCHs in the country, times the required number of States (15). Thus, in 

Exhibit A2.2, the expectation for Rhode Island was (417/146,292) × 15 = 0.0428. Given that the 

cumulative expectation for Rhode Island is 0.7418, we could tell that the random number used 

to start the process was 0.7418 – 0.0428 = 0.6991. Similarly, the expectation for New York was 

equal to (8191/146,292) × 15 = 0.8399, although its cumulative expectation was formed by 

adding this value to the cumulative expectation for Rhode Island. 

The number of times a State was sampled can be represented by the equation: 

(8) sj = Int(cj) - Int(cj-1) 

where c0 is the random number used to begin the process, cj is the cumulative expectation for 

Statej, cj-1 is the cumulative expectation for Statej-1, and Int(cj) resolves to the largest integer 

less than or equal to cj. In Exhibit A2.2, the expression of equation (8) becomes 1 for 

New York, where sj = Int(1.5817) - Int(0.7418) = 1 – 0 = 1. New York, therefore, is selected 

once.44 As shown in the following exhibit, California was sampled twice and 13 States were 

sampled once. One of the two-State combinations (VA + DC) was entered in the sample. As 

expected, all regions were represented. 

 

44 That is to say, 7 sponsors and 30 FDCHs per sponsor were selected from New York. 
A-10 

Exhibit A2.2: State Sampling Procedure and the Resulting Sample of States 

PSU* STATE HOMES REGION EXPECTATION CUMULATIVE SAMPLED 

1 RI 417 1 0.0428 0.7418 0 

2 NY 8,191 1 0.8399 1.5817 1 

3 CT 929 1 0.0953 1.6769 0 

4 MA 5,057 1 0.5185 2.1955 1 

5 NH+VT 730 1 0.0749 2.2703 0 

6 ME 1,277 1 0.1309 2.4012 0 

7 DE 869 2 0.0891 2.4904 0 

8 MD 3,667 2 0.3760 2.8664 0 

9 VA+DC 2,518 2 0.2582 3.1246 1 

10 WV 1,617 2 0.1658 3.2904 0 

11 NJ 700 2 0.0717 3.3622 0 

12 PA 2,119 2 0.2173 3.5794 0 

13 SC 780 3 0.0800 3.6594 0 

14 AL 1,304 3 0.1337 3.7932 0 

15 KY 714 3 0.0732 3.8664 0 

16 FL 2,412 3 0.2473 4.1137 1 

17 NC 3,501 3 0.3590 4.4727 0 

18 GA 3,378 3 0.3464 4.8191 0 

19 MS 528 3 0.0541 4.8732 0 

20 TN 1,558 3 0.1598 5.0330 1 

21 MN 9,679 4 0.9925 6.0255 1 

22 MI 6,664 4 0.6833 6.7087 0 

23 WI 3,605 4 0.3696 7.0783 1 

24 OH 3,411 4 0.3498 7.4281 0 

25 IN 1,751 4 0.1796 7.6077 0 

26 IL 7,725 4 0.7920 8.3997 1 

27 TX 7,011 5 0.7189 9.1186 1 

28 OK 2,944 5 0.3019 9.4205 0 

29 AR 890 5 0.0912 9.5117 0 

30 LA 5,488 5 0.5627 10.0744 1 

31 NM 5,818 5 0.5966 10.6710 0 

32 IA 2,241 6 0.2297 10.9008 0 

33 ND 1,413 6 0.1449 11.0457 1 

34 WY 448 6 0.0459 11.0916 0 

35 SD 652 6 0.0669 11.1585 0 

36 NE 2,721 6 0.2790 11.4375 0 

37 UT 1,975 6 0.2025 11.6400 0 

38 MO 1,694 6 0.1737 11.8137 0 

39 MT 875 6 0.0897 11.9034 0 

40 KS 4,160 6 0.4265 12.3300 1 

41 CO 2,094 6 0.2147 12.5447 0 

42 AZ 3,650 7 0.3743 12.9189 0 

43 WA 3,477 7 0.3565 13.2754 1 

44 CA 19,536 7 2.0031 15.2785 2 

45 NV 254 7 0.0260 15.3045 0 

46 ID 382 7 0.0391 15.3436 0 

47 AK 491 7 0.0503 15.3939 0 

48 OR 2,655 7 0.2723 15.6662 0 

*Note: PSU = primary sampling unit 
A-11 

SELECTING SPONSORS AND HOMES 

Having selected the States, the next step was to select approximately seven sponsors from 

each State for each time the State was selected. Since we had no reason to select sponsors 

within States according to any criteria (e.g., location), the seven sponsors within States were 

chosen randomly. Further, the selection procedure for sponsors was identical to that used to 

select States, with sponsors known to have fewer than 30 homes combined with other 

sponsors. 

Once sponsors were selected, Macro contacted them to find out if they had multiple offices. 

They were asked for the number of homes for which records could be found in each office. One 

office was selected with PPS for each time the sponsor was sampled. This was designed to 

reduce the time the data collector had to spend at the sponsor’s various offices. 

The sampling design was developed in such a way that if a fixed number of FDCHs (in this 

case, 30) were selected from each sponsor, the sample will be approximately self-weighing; 

that is, every FDCH participating in the CACFP nationally will have the same probability of 

selection, hence an equal weight. We describe it as only approximately self-weighing because, 

at every step, size measures were obtained from different sources. 

Also at the time of initial contact, sponsors were asked whether they could provide a list of all 

active FDCHs under their sponsorship (by e-mail or by fax). In the 2005 study, we had hoped to 

be able to come up with a list of homes that were active at any point during that study’s data 

window, June 2004 through May 2005. This turned out to be impossible to obtain; in fact, many 

sponsors could not provide us with the names of the FDCHs that had been active in any of the 

last 3 months. Consequently, to be consistent across the country, we drew our sample based 

on the FDCHs that were active (i.e., received some reimbursements) during May 2005. We 

likewise based our sample on homes reported to be active in that month. For this year’s study, 

the quality control month was September 2006. We drew the sample based on this month, 

asking sponsors to supply us with a list of all active FDCHs for September 2006. The 12-month 

retrospective data window was October 2005 to September 2006 for the current study. 

In drawing the sample of FDCHs, we obtained a list of homes from each sponsor. If the 

sponsor gave us a list of homes active in the designated month (September 2006), we selected 

the sample with equal probability prior to the data collection activities, and gave the data 

collector a list specifying the exact name of each FDCH to be selected. If we were unable to 

obtain this type of list, we provided an ordered list to the data collector, who was instructed to 

select the first 31 homes in the sponsor’s files that were active in the designated month and to 

report the number of homes not active that month. While the selection of 30 homes was the 

original intent, in some cases fewer homes were abstracted, since a sufficient number was not 

actually available. Our procedure called for the abstraction of 1 extra home when feasible at 

each site. These data were examined and processed. After the data were processed, a 

sufficient number was added to the analytic file, as needed across projects, to bring the total 

sample to the intended total. 

WEIGHTING PROCEDURES 

The sampling design was developed to be approximately self-weighing; that is, every FDCH 

participating in the CACFP nationally will have the same probability of selection, hence an equal 

weight. However, in choosing States and sponsors, we relied on home counts from FNS 

initially, then the States. Because of the different sources, the home count varied. In other 

words, in selecting States, we used national summary data provided by FNS. For example, let’s 
A-12 

say that State A was selected and then contacted to provide a list of sponsors and numbers of 

homes per sponsor. The FNS data may have reported 4,000 homes for State A, while the State 

data on homes listed 3,500 homes. Similarly, the State data may have said that Sponsor B had 

300 homes, but when we contacted this sponsor, their list showed 350 active homes. 

The discrepancy in these numbers means that the assumptions under which we chose the 

sample were incorrect. Since State A was chosen on the basis of having 4,000 homes, when it 

had only 3,500 homes, the chance of a home being selected from State A was higher than it 

should have been (4,000 is greater 3,500). To offset this bias, we had to “weight” the 

observations in each State on the basis of the difference between the number of homes that we 

thought was in the State and the number of homes that were actually in the State. 

The same logic applied to the choice of sponsors. In the example, we chose Sponsor B on the 

basis of having 300 active homes, when it actually had 350 homes. We had to make a second 

adjustment in computing the weight of each home from this sponsor to account for this 

difference. We followed similar procedures in last year’s study. 

Finally, there is the issue of homes that were selected for each sponsor. In a handful of cases, 

we found that a home was not active in September 2006, when we collected meal counts at the 

sponsors’ location. As noted, we drew a replacement home, but this factor also affected the 

randomness of the selection process. If 3 of the 30 homes selected from Sponsor B are found 

to be out of scope, we assumed that 10 percent of Sponsor B’s entire list of homes would also 

be out of scope. So the effective number of homes from Sponsor B would not be 350 homes, 

but 315 homes. 

In selecting weights, one uses the probability of selection; but this is a somewhat ambiguous 

term. One can use the unconditional probability of selection, which means that one uses the 

probability of selection of a unit as calculated before the sampling procedure even begins. Or 

one can use the probability of selection at each stage, conditional on the results of the sampling 

at the previous stage. The original intent was to use the unconditional probabilities. However, 

preliminary reports indicate that the intraclass correlation (i.e., the degree to which errors cluster 

in States and sponsors) would be higher than anticipated, and recent findings (Saavedra 2005) 

indicate that the conditional probability of selection is more effective under those circumstances. 

But it is not the case that every home has the same probability of selection at every stage. 

Hence, even with exact counts, using weights would be more effective than using unweighted 

estimates. 

The specific procedures we used in obtaining the weight of an FDCH—correctly or incorrectly 

classified—are described below in equations 9–14. By example, we describe the probability of 

selection of an FDCH from a State that contains less than 1/15 of all FDCHs nationally and from 

a sponsor that administrates less than 1/7 of all FDCHs within the State. The probability of 

selection for the home will be equal to the probability that the State is selected, multiplied by the 

probability that the home’s sponsor is selected (given that the State was selected m times), 

multiplied by the probability that the FDCH is selected (given that the FDCH sponsor was 

selected k times). If data acquired from all sources were completely accurate and 30 homes 

were selected from each sponsor, we would have— 

(9) Pr[State is selected] = 

) ( )

( ) 15 (

N FDCH in Nation

N FDCH in State

∗

 for the probability of State selection; 
A-13 

(10) Pr[Sponsor selected|State selected] = 

) ( )

( ) 7 ( N FDCH in State

N FDCH in Sponsor ∗

for the probability that 

the sponsor is selected given that the State is selected; and 

(11) Pr[FDCH selected|sponsor selected] = 

) ( )

30 (

N FDCH in Sponsor for the probability that the 

FDCH is selected given that the sponsor is selected, where Pr signifies “probability that”, 

N(FDCHs in Nation) denotes the total number of FDCHs in the Nation, and N(FDCHs in State) 

denotes the total number of FDCHs in the selected State, and so forth. 

Multiplying these three probabilities while recalling that we have already determined that we will 

select 30 FDCHs within each of 7 sponsors within each of 15 States, we get ... 

(12) Pr[FDCH is selected] = ( )

3,150

N FDCH in Nation = 146,292

3,150

 = 0.02 

However, there are two sources of information for N(FDCHs in State) and two for N(FDCHs in 

Sponsor), and these sources did not reconcile perfectly. FNS and the sampled States each 

provided a count of FDCHs in the State. Data from FNS describing N(FDCHs in State) were 

used to select the State, while the State provided a count that was used to select sponsors. 

Likewise, both the State and the selected sponsors provided a count of N(FDCHs in sponsor). 

Therefore, the probability of selection of a home is ... 

(13) Pr[FDCH is selected] = 

( )

30

( )

7 ( )

( )

15 ( )

N FDCH in State State N FDCH in sponsor sponsor

N FDCH in sponsor State

N FDCH in Nation FNS

N FDCH in State FNS

⇐

∗

⇐

∗ ⇐

∗

⇐

∗ ⇐

which can be rewritten as... 

(14) 

( )

) ( )

( ) )( ( )( ) 3,150 (

N FDCH in Nation

N FDCH in Sponsor Sponsor

N FDCH in Sponsor State

N FDCH in State State

N FDCH in State FNS

⇐

⇐

⇐

⇐

∗

Where ⇐ means “according to.” Weights differ to the extent that State and sponsor data do not 

reconcile. The inverse of the probability of selection serves as the initial weight, whereby the 

probability of selection is calculated by the equation above. 

The above equations were calculated based on the assumption of the probabilities of States 

being selected and of sponsors being selected within States. It should be added that in 

instances where a State could be selected more than once, we were really dealing with an 

“expectation” and not a true probability. For example, an expectation of 1.8 means that the 

State had a 20 percent probability of being selected only once, and an 80 percent probability of 

being selected twice. However, the weighting scheme presented here used the actual number 
A-14 

of times a State was selected and the actual number of sponsors sampled from that State. 

Likewise, it used the actual number of times a project is selected and the actual number of 

homes selected from that sponsor. Thus if a State was selected twice (as is the case with 

California), the probability of selection of the State was 1, and the probability of selection of the 

sponsor was based on sampling 14 sponsors from the State. An analogous calculation takes 

place if a sponsor was selected more than once. Equations 9–11 become: 

(9)’ Pr[State is selected] = min(1,

) ( )

( ) 15 (

N FDCH in Nation

N FDCH in State

∗

) for the probability of State 

selection; 

(10)’ Pr[Sponsor selected |State selected m 

times] = min(1,m*

) ( )

( ) 7 ( N FDCH in StateN FDCH in Sponsor ∗

) for the probability that the sponsor is 

selected given that the State is selected m times; and 

(11) Pr[FDCH selected |sponsor selected k times ] = 

min(1.(k* 

) ( )

30 (

N FDCH in Sponsor for the probability that the FDCH is selected given that the 

sponsor is selected k times. 

However, as was explained, 30 FDCHs were not selected in every case, so the correct 

probability needed to be multiplied by n/30k, where n is the number of homes actually sampled 

from the sponsor. 

The equations for overall weights proceed analogously. 

VARIANCE ESTIMATION 

Confidence intervals for several estimates (proportions and total dollars) were produced for the 

entire population of homes and for the domains of homes classified by the sponsor as Tier 1 

and Tier 2. The SAS procedure SURVEYMEANS was used to obtain the confidence intervals. 

The SURVEYMEANS procedure* used the Taylor expansion method to estimate sampling 

errors of estimators based on complex sample designs. This method obtains a linear 

approximation for the estimator and then used the variance estimate for this approximation to 

estimate the variance of the estimate itself. When there are clusters or primary sampling units 

(PSUs) in the sample design, the procedures estimates the variance from the variation among 

the PSUs. If the design is stratified, the procedures pool stratum variance estimates to compute 

the overall variance estimate. 
A-15 

For a multistage sample design, the variance estimation method depends only on the first stage 

of the sample design. Thus, the required input includes only first-stage cluster (PSU) and firststage stratum identification. One does not need to input design information about any additional 

stages of sampling. This variance estimation method assumes that the first-stage sampling 

fraction is small or that the first-stage sample is drawn with replacement, as it often is in 

practice. However, the design can apply a finite population correction and allows for the input of 

the sampling rate in each stratum. If the sampling rate varies (unequal probability sampling), as 

it does in this study, one can create strata that approximate a uniform sampling rate. 

The Primary Sampling Units (clusters) in the study were the States. However, one State 

(California) was a certainty, and one (Minnesota) was a near-certainty. In those States, each 

sponsor became a PSU for variance estimation purposes. In Minnesota, one of the sponsors, 

was sampled four times because it was large. For Minnesota, this large sponsor was divided 

into four PSUs, and two of the smaller ones were combined. 

The clusters were then paired up into "strata" assigned so that clusters in the same strata were 

of the same kind (State or sponsor), in the same State (for sponsors) and with similar 

probabilities of selection. As in the previous study, there were 32 clusters and 16 strata this 

year. The average probability of selection of the two clusters in a stratum were entered as the 

sampling rate of the stratum. This pairing of clusters is common in many variance estimation 

procedures, particularly when one needs to use a finite population correction. 

One kind of estimate developed for the study was the proportion of errors, obtained for the total 

population and the Tier 1 and Tier 2 domains separately. The estimates (for each Tier and a 

total) were obtained by adding the weights of the homes incorrectly classified and dividing the 

result by the sum of the weights. 

The second estimate produced was an estimate of total dollar errors. In this case, the average 

was first obtained and multiplied by the reported total number of homes obtained from the 

National Data Bank for FY 2006. This way, the variance of the estimates of the total number of 

homes in the program did not have to be included in the variance. 

The variance estimates had their own error of estimate. As a result, when calculating the 

confidence intervals, one needed to take into account the variance of the variance estimates. 

To do this, one has to first obtain the degrees of freedom (the number of clusters minus the 

number of strata) and multiply the standard error by the t value for the 90 percent confidence 

interval for the degrees of freedom in question. 
Appendix 3. 

Tiering Determination Instrument 
A-16 

FDCH Name: Study ID #: ST Part II A – FDCH Monthly Meal Reimbursement (meal count) Requested from the State Complete the table below for the FDCH name above. Obtain all twelve months (October2005-September 2006) if accessible at data collection site. collect data for as many months as you can. Data for September 2006 is required. If, after your initial conversation with the sponsor contact, you find that this sponsor uses blended rates for this FDCH, indicate the conversion factor 

methods below: 

1) percent of children eligible for high reimbursement rate: % of children:______, OR 2) specific rates for each type of meal: breakfast rate:_____ lunch/supper rate: _____ snack rate: _____ , OR 3) number of breakfasts in one month and total reimbursements for these breakfasts: # of breakfasts: _____ total reimbursement: _____  September 2006 August 2006 July 2006  Tier I Tier II Tier II blended Tier I Tier II Tier II blended Tier I  adding total adding total adding total adding total adding total adding total adding total # of breakfasts # of snacks # of lunch/ supper June 2006 May 2006 April 2006  Tier I Tier II Tier II blended Tier I Tier II Tier II blended Tier I  adding total adding total adding total adding total adding total adding total adding total # of breakfasts # of snacks # of lunch/ supper  March 2006 February 2006 January 2006  Tier I Tier II Tier II blended Tier I Tier II Tier II blended Tier I  adding total adding total adding total adding total adding total adding total adding total # of breakfasts # of snacks # of lunch/ supper  December 2005 November 2005 October 2005  Tier I Tier II Tier II blended Tier I Tier II Tier II blended Tier I  adding total adding total adding total adding total adding total adding total adding total # of breakfasts # of snacks # of lunch/ supper 
A-17 

 Study ID #: 

 

Part II B – FDCH Basic Information Complete One Form For Each FDCH 

Term use

FDCH Name: 

Sponsor Assigned FDCH ID this may be a name or a number, or not 

be available) optional: ID #: 

FDCH Address: 

For Tier I: Date of most recent tiering 

Most Recent Tiering Determination determination: (circle one): Tier I Tier II For Tier II: Date of most recent tiering 

determination optional: 

If Tier II, is there evidence that the FDCH requested a new tiering determination in the last three years? (circle one) 

Yes No N/A If yes, date of request for new tiering determination: 

Photocopy needed? Yes. Photocopy most recent tiering determination including the date. If Tier II and there is evidence that FDCH 

requested a new tiering determination in the last three years, photocopy request. Photocop

If FDCH is being dropped (after acquiring permission from headquarters), complete the section below Reason for dropping FDCH*: Who approved dropping FDCH? FDCH being replaced by (study ID # and name of replacement): *CODES FOR DROPPING FDCH: 1) No meal reimbursement during study time 2) Other (specify) ___________________________________ In most instances you will collect data in Parts III – VI of this form for FDCH that have a tier I classification. For a tier II FDCH if there is documenta

to gain Tier I status (e.g., copies of income tax forms), complete parts III-VI of this form as you would for a tier I FDCH. 
A-18 

 Study ID #: 

 

Tiering Determination 

Part III – Tiering Determination by Area Eligibility – School Boundary Area If there is evidence that school boundary information was collected to make the most recent tiering determination, complete the table below. 

“NONE” at the bottom of the table. 

Full Name of School: Address of School, if available optional: If information is available in the file, circle all grades included in the school named above optional: Pre –K K 1 2 3 4 5 6 7 8 9 10 11 12 A. B. C. D. E. F. G

Type of Documentation 

Present at Sponsor Site? Y/N 

Dated? Y/N 

If dated, enter Date (mm/dd/yyyy) Date may be school year, e.g. 2004-2005 

Initial or Signed? Y/N 

Photocopy Needed? 

Doapr

Documentation of School Status 

State or county list of schools showing this school meets the low-income eligibility standard* YES Letter from school official to sponsor indicating school has 50% of children eligible for free/reduced meals YES Other (specify): ________________________________ YES NONE (check here):_____________ YES 

Documentation That FDCH Is In School Boundary Area 

Official School Boundary Identifying map (date may be school 

year e.g., 2004-2005) YES 

Letter/Memo from school official or state agency indicating that previous years’ map is still valid YES Page(s) from directory linking FDCH address to elementary school** YES Memo to the file about information from school/state official YES Printed copy of website information YES Other (specify): _______________________________ YES If NONE you must check here: __________ 

*The low income eligibility standard is at least 50% of children eligible for free or reduced priced meals. This can be either a list of all school

children per school OR a list of the names of the schools that meet or surpass the 50% standard. Photocopy the page that displays the relevant ele

**The source of these pages must be from a public agency such as the state Board of Education, local area School District or county busing coordi
A-19 

 Study ID #: 

 

Tiering Determination (continued) Part IV - Tiering Determination by Area Eligibility – Census Block Group If there is evidence that census block group information was collected to make the most recent tiering determination, complete the table below. If 

“NONE” at the bottom of the second section of the table. 

Documentation Showing Location Of The Home In A 2000 Census Block Group 

Present at Site? (Y/N) 

PhNe

2000 block group boundary map from either census or geo-mapping computer software program YEDocument showing that this address is in a specific census block group YEOther (specify): YEIf NONE, you must check here: ___________ 

Documentation Showing That The Block Group Meets Income Eligibility Standard* 

A page from a document showing the census block group is income-eligible* YEA map of the census block group indicating (possibly through color coding) the census block group is incomeeligible* YEOther (specify) YEIf NONE, you must check here: ___________ 

Other Question 

Is there any documentation that the sponsor rejected using the school census block option because the school was 

in a rural area, had bused in students or was a magnet school? (check one) Yes ______________ No ________________ 

*at least 50% of children are eligible for free and reduced meals
A-20 

 Study ID #:  

Tiering Determination (continued) Part V – Tiering Determination by Eligibility of Provider - Categorical If there is evidence that information was collected about the provider’s participation in any of the programs listed below to make the most recent 

table below. If no such evidence is found, check “NONE” at the bottom of the table. 

Type of Documentation 

Present at Site? (Y/N) 

Dated? (Y/N) 

Expiration Date (mm/dd/yyyy) 

Initialed or Signed? (Y/N) 

Case Num(Y/N) 

Food Stamps 

Certification / Letter / Print out from Food Stamp office Authorization to participate card Memo or record of phone call from agency official confirming eligibility 

TANF / State Welfare 

Certification / Letter / Print out from TANF office Memo or record of phone call from agency official confirming eligibility 

Food Distribution Programs on Indian Reservations (FDPIR) 

Document that confirms participation in this program 

Other 

Document that confirms participation in other government welfare program (specify): If NONE , you must check here: __________ 
A-21 

 Study ID #: 

 

Tiering Determination (continued) Part VI A – Tiering Determination by Eligibility of Provider – Income, Information used by sponsor to make latest tiering determination If there is evidence that information on provider income was collected to make the most recent tiering determination, complete the table below. check the appropriate box at the bottom of each section. This information may be found on form that displays latest tiering determination, application, worksheet or other sponsor kept record. Type of Information 

Amount / Number on Form 

Frequency Y/N If yes, date (mm/dd/yyyy) Pho

Nee

Income Amount Used In Tiering Determination 

Total household income on tiering determination form or worksheet $ Yes

alre

If no indication on tiering determination form, worksheet or other sponsor kept record of what amount of household income was used in tiering determination, check here: __________ 

Household Size Used In Tiering Determination 

Number of household members on tiering determination form or worksheet # Yes

alre

If no indication on tiering determination form, worksheet or other sponsor kept record of what number of household members was used in tiering determination, check here: ___________ 

Key Questions (YOU MUST RECORD A RESPONSE) 

Is the SSN of the adult who signed the form included on the form? Is the form signed by an adult household member? Yes

alre

**** Frequency of Income on Documentation - A=annual M=monthly TW=every two weeks TM=twice a month W=weekly D=daily  O=any other frequency (specify in table) 
A-22 

 Study ID #: 

 

Tiering Determination (continued) Part VI B – Tiering Determination by Eligibility of Provider – Income Documentation found in file Documentation found in file for provider income Complete one form for each household member who has income. (Exception: If a tax form is used to verify income and a joint return was filed, pwrite the names of the persons filing jointly and insert the relationship to provider.) If the household member listed under “Member Name” has mit is not included on a tax form that has already been listed as documentation, fill out an additional row for documentation found for each source tax form. Type of Documentation Relationship to Provider* Income Code** Documentation in File? (Y/N) Type of Documentation in File*** Date of Documentation (mm/dd/yyyy) Amount of Income on Doc.+ Net or Gross? (N/G) F

y A

Member Name 

 

Documentation Of Other Income For The Person Listed Under “Member Name” Above 

  

If NONE you must check here): ______ 

If Tax Form Filed Jointly, Insert Name Of Joint Filer On Tax Form And Relationship To Provider * Relationship to Care Provider - CP=care provider SP=spouse of CP CH=child of care provider P=parent of care provider O=o** Income Codes - E=earned, wages, self-owned business WUC=welfare, unemployment, child support, alimony PS=pensions, re

other earned income (specify in table) 

*** 

Type of documentation in file - T=Federal tax form CT=schedule C of Federal tax form S=State tax form PS=pay stubs PO=pri

LE=letter from employer BL=benefit letter SF=statements from DC families about payment to provider D=statement from provide(specify in table) 

**** Frequency of Income on Documentation - A=annual M=monthly TW=every two weeks TM=twice a month W=weekly D=daily O=a

(specify in table) 

+ If abstracting data tax form, use amount on line 22 from Form 1040, line 4 from Form 1040 EZ or line 15 from Form 1040A in the Amount o

If abstracting data from Form 1040 Schedule C to document self-employment income, use line 31; or if Schedule C-EZ is used, use line 3 i
A-23 

 Study ID #:  

Notes About Meal Counts: Notes About Tiering Determination Documents: Other Notes: 
Appendix 4. 

Examples of Poor Documentation of 

Tier I Status 
A-24 

Example 1: No Date on School Map Provided in FDCH File 
A-25 

Example 2: Date on School Map in the FDCH Prior to 2002 
A-26 

Example 3: Unofficial School Map in FDCH File, with 

No Signed Supporting Documentation 
A-27 

Example 4: School Linking to FDCH is FRP Ineligible 

Note: the Elementary School identified for the FDCH is Mountainview Elementary, 

which only has 34% of the students qualifying for a free or reduced price meal.
A-28 

Example 5A: Self-Reported Ledger Sheet 
A-29 

Example 5B: Self-Reported Ledger Sheet 
A-30 

Example 6: Self-Declared Ledger Sheet