National Household 

Education Surveys 

Program of 2005 

Nonresponse Bias in 

the 2005 National 

Household Education 

Surveys Program 

U.S. Department of Education 

Institute of Education Sciences 

NCES 2007-016 

National Household 

Education Surveys 

Program of 2005 

Nonresponse Bias in 

the 2005 National 

Household Education 

Surveys Program 

November 2006 

Shelley Brock Roth 

Jill M. Montaquila

Westat 

Chris Chapman

National Center for Education Statistics 

U.S. Department of Education 

Institute of Education Sciences 

NCES 2007-016 
U.S. Department of Education

Margaret Spellings 

Secretary

Institute of Education Sciences 

Grover J. Whitehurst 

Director

National Center for Education Statistics

Mark S. Schneider 

Commissioner

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Suggested Citation 

Roth, S., Montaquila, J., Chapman, C. (2006). Nonresponse Bias in the 2005 National Household 

Education Surveys Program. Technical Report. (NCES 2007-016). U.S. Department of Education, 

National Center for Education Statistics. Washington, DC: U.S. Government Printing Office.

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Content Contact 

Christopher Chapman 

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nhes@ed.gov
iii 

Executive Summary 

The theory of sampling that is the basis for the majority of surveys conducted for the federal 

government assumes that accurate responses are obtained for all the sampled units. Surveys have always 

had some level of nonresponse, thus violating this assumption, and the level of nonresponse has been 

increasing over time. Nonresponse bias is a function of the nonresponse rate and the difference between 

respondents and nonrespondents. To the extent that those who respond to surveys and those who do not 

are different in important ways, there is a potential for nonresponse biases in estimates from survey data. 

As survey response rates decline, understanding the relationship between response rates and nonresponse 

bias has become even more important. One approach to understanding the relationship is to conduct 

nonresponse bias studies. This report documents a nonresponse bias study for the 2005 National 

Household Education Surveys Program (NHES:2005). The goal of the research was to investigate the 

potential for nonresponse bias in estimates from the NHES:2005 surveys. 

NHES, a survey program sponsored by the National Center for Education Statistics (NCES) 

in the Institute of Education Sciences, U.S. Department of Education, is designed to study educational 

issues that cannot be addressed in institutional surveys. The NHES surveys conducted in 2005 were the 

Early Childhood Program Participation Survey (ECPP-NHES:2005), After-School Programs and 

Activities Survey (ASPA-NHES:2005), and Adult Education Survey (AE-NHES:2005). ECPP gathered 

information on the nonparental care arrangements and educational programs of preschool children. ASPA 

addressed nonparental care and activities during the after-school hours of elementary- and middle schoolage children. AE addressed participation in formal adult educational activities and informal learning 

activities done for personal interest. 

The estimates from NHES:2005 are subject to bias because of unit nonresponse to both the 

Screener survey (used to determine household eligibility for sampling) and the extended interview 

surveys, as well as nonresponse to specific items. Generally speaking, the best approach to minimizing 

nonresponse bias is to plan and implement data collection procedures aimed at achieving high response 

rates. For NHES:2005, such procedures included extensive training of the interviewers, advance mailings 

to the respondents, effective call scheduling strategies, and, where necessary, refusal conversion methods 

that included recontacting households by both telephone and mail if mailable addresses could be obtained. 

However, because some nonresponse occurs even with the best strategies, statistical adjustments are 

necessary to minimize the potential for nonresponse bias in the survey estimates. 
iv 

This report includes assessments of the potential for both unit and item nonresponse bias. 

The analysis of unit nonresponse bias showed no evidence of bias in the estimates considered from the 

ECPP and ASPA Surveys. For the AE Survey, the only evidence of unit nonresponse bias is in estimates 

of sex; females were more likely to respond than males. The weighting class adjustment for nonresponse 

to the AE Survey used sex in forming the weighting classes (see Hagedorn et al. forthcoming for details.) 

and should, therefore, reduce this bias. 

The analysis of item nonresponse bias included two components: (1) a comparison of means 

or distributions, including imputed values versus excluding imputed values; and (2) a comparison of 

means or distributions based on extreme assumptions to the original means or distributions. It is important 

to consider the two components of the item nonresponse bias analysis in tandem. The former component 

of the item nonresponse bias analysis revealed no important differences1

, thus suggesting that there was 

no reduction in item nonresponse bias. The latter component did reveal the potential for item nonresponse 

bias, if the item nonrespondents differ considerably from the respondents. However, it is that particular 

situation in which the hot-deck would be expected to be most effective in reducing item nonresponse bias; 

by using variables to form hot-deck cells that are associated with either the item itself or its item response 

propensity, the hot-deck reduces item nonresponse bias. Therefore, taken together, these two components 

of the item nonresponse bias analysis suggest that the likely scenario is that there was no substantial item 

nonresponse bias, and that the extreme assumptions imposed in this analysis are unrealistic. 

It is important to note that although no evidence of nonresponse bias was found in this 

analysis, the analysis was limited. Nonresponse bias could be present in estimates not considered in this 

analysis, but most of the techniques used in this evaluation could be applied by analysts to examine the 

potential for nonresponse bias in their estimates. 

 

1

 None of the differences were 3 percentage points or more and statistically significant at the α = 0.05 level. 
v 

TABLE OF CONTENTS 

Chapter Page

 Executive Summary......................................................................................... iii 

1 Introduction...................................................................................................... 1 

1.1 Overview of the National Household Education Surveys Program.... 2 

1.2 Relationship Between Response Rates and Nonresponse Bias .......... 3 

1.3 Analysis Methods ............................................................................... 5 

2 Unit Nonresponse Bias .................................................................................... 7 

2.1 Unit Response Rates .......................................................................... 7

2.2 Analysis of Characteristics Associated with Unit Response 

 Propensities......................................................................................... 10

2.3 A Comparison of Estimates Based on Adjusted and Unadjusted 

 Weights............................................................................................... 12 

 2.3.1 Estimates of Characteristics for the ECPP and ASPA 

 Interviews ..................................................................................... 15 

 2.3.2 Estimates of Characteristics for the AE Interview ...................... 15 

3 Item Nonresponse Bias .................................................................................... 33 

3.1 Item Response Rates and Items Included in this Analysis.................. 35

3.2 Assessment of Means or Distributions for Items With and Without 

 Imputed Values................................................................................... 37 

3.3 Using Extreme Assumptions to Assess the Potential for Item 

 Nonresponse Bias ............................................................................... 46 

4 Conclusions...................................................................................................... 57 

 References........................................................................................................ 59 
vi 

TABLE OF CONTENTS (continued) 

List of Tables 

Table Page 

 1 Screener nonresponse adjustment cells: 2005 ...................................................... 9 

 2 ECPP interview nonresponse adjustment cells: 2005............................................. 13 

 3 ASPA interview nonresponse adjustment cells: 2005............................................ 13 

 4 AE interview nonresponse adjustment cells: 2005................................................. 14 

 5 ECPP comparison of estimates based on nonresponse-adjusted weights and 

 unadjusted weights for children age 0 to 6 who are enrolled in preschool or 

 not enrolled, by child and family characteristics: 2005........................................ 16 

 6 ASPA comparison of estimates based on nonresponse-adjusted weights and 

 unadjusted weights for children age 3 to 15 who are enrolled in kindergarten 

 through 8th grade, by child and family characteristics: 2005................................ 18 

 7 ECPP comparison of estimates of selected characteristics based on nonresponse- 

 adjusted weights and unadjusted weights for children age 0 to 6 who are 

 enrolled in preschool or not enrolled, by race/ethnicity: 2005............................. 20 

 8 ASPA comparison of estimates of selected characteristics based on nonresponse- 

 adjusted weights and unadjusted weights for children age 3 to 15 who are 

 enrolled in kindergarten through 8th grade, by race/ethnicity: 2005 ................... 23 

 9 AE comparison of estimates based on nonresponse-adjusted weights and 

 unadjusted weights for adults, by demographic characteristics: 2005................ 25 

 10 AE comparison of estimates based on nonresponse-adjusted and unadjusted 

 weights for adults who took part in various adult education activities in a 

 12-month period, by race/ethnicity: 2005.............................................................. 27 

 11 AE comparison of estimates based on nonresponse-adjusted and unadjusted 

 weights for adults who took part in various adult education activities in a 

 12-month period, by sex: 2005............................................................................... 29 

 12 AE comparison of estimates based on nonresponse-adjusted and unadjusted 

 weights for adults who took part in various adult education activities in a 

 12-month period, by educational achievement: 2005........................................... 30 

 13 ECPP items included in the nonresponse bias analysis: 2005................................ 35 
vii 

TABLE OF CONTENTS (continued) 

List of Tables (continued) 

Table Page 

 14 ASPA items included in the nonresponse bias analysis: 2005............................... 36 

 15 AE items included in the nonresponse bias analysis: 2005.................................... 36 

 16 Means for items with and without imputed values: 2005....................................... 38 

 17 Relative frequency distributions for items with and without imputed values: 2005 39 

 18 Comparison of original and extreme imputed value variables estimates, for items 

 with one extreme imputed value variable: 2005..................................................... 48 

 19 Comparison of original and extreme imputed value variable estimates, for items 

 with low and high extreme imputed value variables: 2005 ................................... 50 

 
viii 

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1 

1. Introduction 

The theory of sampling that is the basis for the majority of surveys conducted for the federal 

government assumes that accurate responses are obtained for all the sampled units. Surveys have always 

had some level of nonresponse, thus violating this assumption, and the level of nonresponse has been 

increasing over time. For example, Atrostic, Bates, Burt, and Silberstein (2001) report that the rates of 

nonresponse were increasing for in-person household surveys conducted by the U.S. Census Bureau at the 

end of the 20th century. In a random digit dial (RDD) telephone survey, Curtin, Presser, and Singer 

(2005) state that the response rates to the Survey of Consumer Attitudes declined by an annual rate of 

three-quarters of a percentage point from 1979 to 1996, and by 1.5 percentage points per year on average 

from 1996 to 2003. 

To the extent that those who respond to surveys and those who do not are different in 

important ways, there is a potential for nonresponse biases in estimates from survey data. As survey 

response rates decline, understanding the relationship between response rates and nonresponse bias has 

become even more important. One approach to understanding the relationship is to conduct nonresponse 

bias studies. This report documents a nonresponse bias study for the 2005 National Household Education 

Surveys Program (NHES:2005). The goal of the research is to investigate the potential for nonresponse 

bias in estimates from the NHES:2005 surveys. This analysis is similar to analyses undertaken to evaluate 

the potential for nonresponse bias in the NHES:1999 and NHES:2001 surveys. (See Nolin et al. (2000) 

and Nolin et al. (2004), respectively). A more extensive study of nonresponse bias in NHES:2001, which 

included an examination of nonresponse bias under hypothetical data collection scenarios involving lower 

levels of effort (resulting in lower response rates), is described in Brick et al. (forthcoming). 

An overview of the NHES:2005 surveys is given in the next section, followed by a 

discussion of the relationship between response rates and nonresponse bias (section 1.2), and a discussion 

of the analysis methods used in this study (section 1.3). Section 2 contains a discussion of unit 

nonresponse bias, including unit response rates (section 2.1), an analysis of characteristics associated with 

unit response propensities (section 2.2), and a comparison of estimates based on adjusted and unadjusted 

weights for the ECPP and ASPA surveys (section 2.3.1), as well as the AE survey (section 2.3.2). Section 

3 contains a discussion of item nonresponse bias, including item response rates and items included in the 

analysis (section 3.1), an assessment of means or distributions for items with and without imputed values 
2 

(section 3.2), and a discussion of using extreme assumptions to assess the potential for item nonresponse 

bias (section 3.3). Conclusions are given in section 4. 

1.1 Overview of the National Household Education Surveys 

Program 

NHES, a survey program sponsored by the National Center for Education Statistics (NCES) 

in the Institute of Education Sciences, U.S. Department of Education, is designed to study educational 

issues that cannot be addressed in institutional surveys. For example, studies of the educational 

experiences of young children cannot be conducted solely through institutional surveys because children 

may be educated or cared for in a variety of formal and informal settings and may be cared for only in 

their own homes. Similarly, adults may participate in educational activities in a variety of settings, 

including traditional schools or colleges, community organizations, businesses, and so on; therefore, 

institutional surveys are not suitable to address the broad range of adult education activities. NHES 

collects timely information on specific education topics from a relatively large, targeted sample of 

households and has been conducted approximately every other year since 1991. NHES gathers data on 

several important topics on a rotating basis. For instance, adult education and early childhood program 

participation have been the focus of several NHES surveys. One-time surveys on current issues, such as 

school safety and discipline and civic involvement, have been conducted as well. 

The NHES surveys are RDD telephone surveys of households in the United States. 

Interviews are administered using computer-assisted telephone interview (CATI) technology, which is a 

data collection methodology specifically designed so that relatively complex questionnaires can be 

handled smoothly and efficiently. Previous NHES surveys have been conducted in 1991, 1993, 1995, 

1996, 1999, 2001, and 2003. All surveys were conducted at the same time of the year, winter to early 

spring. The 2005 administration was conducted by Westat, a social science research organization, from 

January 3 through April 24, 2005. 

The NHES surveys conducted in 2005 (NHES:2005) were the Early Childhood Program 

Participation Survey (ECPP-NHES:2005), After-School Programs and Activities Survey (ASPANHES:2005), and Adult Education Survey (AE-NHES:2005).2

 ECPP gathered information on the 

 

2

 Hereafter, these are referred to as simply the ECPP, ASPA, and AE surveys, respectively 
3 

nonparental care arrangements and educational programs of preschool children. ASPA addressed 

nonparental care and activities during the after-school hours of elementary and middle school-age 

children. AE addressed participation in formal adult educational activities and informal learning activities 

done for personal interest. 

NHES provides national cross-sectional estimates for the 50 states and the District of 

Columbia. The NHES design also yields estimates for subgroups of interest for each survey, for example, 

age or grade for children, educational participation status for adults, and race and Hispanic origin for all 

populations of interest. In addition to providing cross-sectional estimates, NHES is also designed to 

provide estimates of change over time in key statistics. The survey instruments are designed to address 

the selected issues in sufficient detail so that analyses can be performed to help explain the phenomena of 

interest. 

1.2 Relationship Between Response Rates and Nonresponse 

Bias 

The estimates from NHES: 2005 are subject to bias because of unit nonresponse to both the 

Screener3

 and the extended interview surveys, as well as nonresponse to specific items. Generally 

speaking, the best approach to minimizing nonresponse bias is to plan and implement data collection 

procedures aimed at achieving high cooperation rates. For NHES:2005, such procedures included 

extensive training of the interviewers, advance mailings to the respondents, effective call scheduling 

strategies, and, where necessary, refusal conversion methods that included recontacting households by 

both telephone and mail if mailable addresses could be obtained. However, because some nonresponse 

occurs even with the best strategies, statistical adjustments are necessary to minimize the potential for 

nonresponse bias in the survey estimates. 

The term bias has a specific technical definition in this context. Bias is the expected 

difference between the estimate from the survey and the actual population value. For example, if all 

households were included in the survey, the difference between the estimate from the survey and the 

actual population value (which includes the responses of persons who did not respond to the survey) is the 

 

3

 The Screener was completed by a member of the household who was age 18 or older. It was used to determine whether sampled telephone 

numbers belonged to households, gather information needed to sample household members for interviews, select the appropriate parent or 

guardian for ECPP or ASPA interviews, and collect household information where no one was sampled for an extended interview. 
4 

bias due to nonresponse. Since NHES is a sample survey, the bias is defined as the expected or average 

value of this difference over all possible samples. 

A deterministic view of nonresponse4

 implies that the population can be partitioned so that 

every unit can be classified into respondent and nonrespondent strata, irrespective of whether the unit was 

sampled (Cochran 1977, p. 361-362). For an estimate of a mean, a common way of describing the 

relationship between the response rate and nonresponse bias under this approach is 

bias(yr ) = Pm {Yr − Ym }, 

where r y is the estimated mean of characteristic y based on the respondents only, Pm is the proportion of 

the population in the nonrespondent stratum, Yr is the mean of the characteristic in the respondent 

stratum, and Ym is the mean of the characteristic in the nonrespondent stratum. This expression shows 

that, under this deterministic viewpoint, the nonresponse bias of an estimated mean depends on the 

relative sizes of the strata and the difference in the mean of the characteristic between the two strata. 

Thus, nonresponse bias can be substantial when two conditions hold. First, the differences 

between the characteristics of respondents and nonrespondents must be relatively large. For example, 

consider estimating the percentage of adults who participated in an adult education activity in the past 

year. If the participation rate is nearly identical for both respondents and nonrespondents, then the 

nonresponse bias of the estimate will be negligible. 

Second, the nonresponse rate must be relatively high. If the nonresponse rate is very low 

relative to the magnitude of the estimates, then the nonresponse bias in the estimates will be small, even if 

the differences in the characteristics between respondents and nonrespondents are relatively large. For 

example, if the nonresponse rate is only 2 percent, then estimates of totals that comprise 20 or 30 percent 

of the population will not be greatly affected by nonresponse, even if the differences in these 

characteristics between respondents and nonrespondents are relatively large. It is important to realize that 

this condition requires the nonresponse rate to be large relative to the size of the estimates. If the estimate 

 

4

 An alternative perspective of nonresponse, not discussed here, is the stochastic viewpoint. See Brick et al. (forthcoming) for a discussion of this 

viewpoint. 
5 

is for a small domain or subgroup, then even a relatively low rate of nonresponse can result in important 

biases if the differences between respondents and nonrespondents are large. 

1.3 Analysis Methods 

The nonresponse bias study for NHES:2005 involves two components: an examination of 

bias due to unit nonresponse (discussed in section 2) and an examination of bias due to item nonresponse 

(discussed in sections 3 and 4). Details of the study design and analysis methods for each of these 

components are provided in context in the respective sections. In this section, we describe general criteria 

and methods used throughout the analysis. 

The estimates and standard errors presented in this report were produced using WesVar 

software and a jackknife replication procedure (Westat 2000). The tests of significance used are based on 

two-tailed tests using Student’s t statistics for the comparison of individual estimates and for bivariate 

relationships. The type I error rate used for all tests was α = 0.05 . Where appropriate (for example, in the 

comparisons of nonresponse adjusted and unadjusted estimates discussed in section 2.3), the standard 

error in the denominator of the test statistic was computed to account for correlations in the estimates. 
6 

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7 

2. Unit Nonresponse Bias 

As noted in section 1.2, nonresponse bias can be substantial when the nonresponse rate is 

relatively high and the nonrespondents differ considerably from the respondents. This section contains an 

evaluation of the potential for bias due to unit nonresponse. In many surveys, such an evaluation would 

contain an examination of differences between unit respondents and the full sample in characteristics 

available on the sampling frame. However, in RDD samples, the sampling frame data are limited to 

general characteristics of the telephone exchange (the area served by the 3-digit prefix of a telephone 

number), and in the case of NHES:2005, there is also the temporal consideration that these characteristics 

pertained at the time of the 2000 decennial census. For these reasons, there were no characteristics 

available for the full frame and the respondents for analysis. 

Section 2.1 contains an examination of unit response rates. An analysis of characteristics 

associated with unit response propensities is given in section 2.2. An analysis conducted to inform the 

nonresponse adjustment (discussed in section 2.2) identified the characteristics most associated with unit 

nonresponse (with these sampling frame variables considered as potential candidates), and those 

characteristics were used in the adjustment. To examine the effect of weighting on unit nonresponse bias, 

section 2.3 contains a comparison of estimates based on nonresponse adjusted and unadjusted weights for 

the three surveys, ECPP, ASPA, and AE. 

2.1 Unit Response Rates

A unit response rate is the ratio of the number of units with completed interviews (for 

example, the units could be telephone numbers, households, or persons) to the number of units sampled 

and eligible for the interview. In some cases, these rates are easily defined and computed, while in other 

cases the numerators or denominators of the ratio must be estimated. 

For reporting the results from NHES:2005, the overall unit response rate5

 indicates the 

percentage of possible interviews that were completed taking all survey stages into account, while the unit 

 

5

 In earlier NHES publications, this was referred to as simply the response rate. 
8 

response rate6

 measures the percentage of interviews that were completed for a specific stage of the survey. 

For example, household members were identified for interviews in a two-stage process. Screener interviews 

were conducted to enumerate and sample household members, and then questionnaires were administered 

for the sampled members. The Screener unit response rate is the ratio of the number of households with 

completed Screener interviews to the estimated number of households in the sample. If no household 

member completed the first-stage Screener, then no members could be sampled for other interviews. Under 

this design, the unit response rate for the second stage (ECPP, ASPA, or AE interviews) is the percentage of 

sampled persons who completed these interviews. The overall unit response rate is the product of the firstand second-stage unit response rates (i.e., the Screener unit response rate multiplied by the extended 

interview unit response rate). 

Unit response rates and overall unit response rates can be either unweighted or weighted. The 

unweighted rate, computed using the raw number of cases, provides a useful description of the success of 

the operational aspects of the survey. The weighted rate, computed by summing the weights (usually the 

reciprocals of the probability of selecting the units) for both the numerator and denominator, gives a 

better description of the success of the survey with respect to the population sampled since the weights 

allow for inference of the sample data (including response status) to the population level. Both rates are 

usually similar unless the probabilities of selection and the unit response rates in the categories with 

different selection probabilities vary considerably. All of the unit response rates discussed in this report 

are weighted. 

One Screener interview is given for all survey components. The Screener unit response rate 

was 67 percent. This rate is multiplied by the ECPP, ASPA, and AE unit response rates to obtain overall 

unit response rates for each of those survey components. Table 1 in section 2.2 shows the nonresponse 

adjustment cells and estimated response rates for each cell for the Screener. 

The ECPP Survey had a unit response rate of 84 percent and an overall unit response rate of 

56 percent (the product of the Screener unit response rate, 67 percent, and the ECPP unit response rate, 84 

percent). The bulk of the unit nonresponse for the ECPP interview was due to refusal of the 

parent/guardian to respond (47.9 percent of nonresponse). Other reasons for ECPP interview nonresponse 

 

6

 In earlier NHES publications, this was referred to as the completion rate. 
9 

Table 1. Screener nonresponse adjustment cells: 2005 

Cell 

Mailable 

status 

Number of 

answering 

machine 

messages 

left 

Percent 

White 

Census 

division

Percent 

Hispanic

Census 

region

Median 

home value

Percent 

with 

income 

$75,000 or 

higher

Percent 

homeowners 

MSA 

Status

Estimated 

response 

rate 

(percent)1

 

1 1 0 0,1 0,2,5,6,7,9 † † † † † † 64.9

2 1 0 0,1 1,3,4,8 † † † † † † 74.5

3 1 0 2,3 † 0,1 † † † † † 70.3

4 1 0 2,3 † 2,3 † † † † † 63.2

5 1 0 2,3 † 4,5 † † † † † 66.4

6 1 0 2,3 † 6-9 † † † † † 74.0

7 1 0 4-6 † † 1 † † † † 65.6

8 1 0 4-6 † † 2-4 † † † † 76.0

9 1 0 7,8 † † 1 † † † † 73.2

10 1 0 7,8 † † 2-4 † † † † 81.5

11 1 0 9 † † 1 † † † † 80.3

12 1 0 9 † † 2,4 † † † † 85.4

13 1 0 9 † † 3 † † † † 82.8

14 1 1 0-2 † † † † † † † 57.3

15 1 1 3,4 † † † 0-6 † † † 66.8

16 1 1 3,4 † † † 7-9 † † † 56.5

17 1 1 5,6 † † † † 0-2 † † 69.0

18 1 1 5,6 † † † † 3-9 † † 61.9

19 1 1 7,8 † † 1 † † † † 62.8

20 1 1 7,8 † † 2-4 † † † † 70.3

21 1 1 9 0-2,5,9 † † † † † † 70.1

22 1 1 9 3,6,7 † † † † † † 74.3

23 1 1 9 4,8 † † † † † † 78.2

24 1 2 † † † † † † 0-6 † 50.6

25 1 2 † † † † † † 7-9 † 57.3

26 1 3,4 † † 1-4 † † † † † 93.0

27 1 3,4 † † 5-9 † † † † † 72.6

28 1 3,4 † † 0 † † † † 1-3 97.2

29 1 3,4 † † 0 † † † † 4,5 100.0

30 2 0 † † † † † † † † 46.0

31 2 1 † † † † † † † 1-4 51.2

32 2 1 † † † † † † 0-7 5 56.1

33 2 1 † † † † † † 8,9 5 72.8

34 2 2-4 † † † † † † † † 43.1

35 3,4 † † † † † † † † † 39.3

† Not applicable. In these cases, the cell consisted of all values of the particular variable. 

1 The estimated response rate is the number of completed interviews divided by the sum of the number of completed interviews, nonresponses, 

and 22 percent of the unresolved telephone numbers, weighted by the probability of selection. (See Hagedorn et al. forthcoming.) 

NOTE: Category codes were as follows: Mailable Status: 1 = valid address obtained; 2 = address not obtained; 3,4 = postmaster return. 

Percent White, Percent Hispanic, Percent with income $75,000 or higher, and Percent homeowners: 0 = less than 10 percent, 1 = 10 to 19 percent, 

2 = 20 to 29 percent, 3 = 30 to 39 percent, 4 = 40 to 49 percent, 5 = 50 to 59 percent, 6 = 60 to 69 percent, 7 = 70 to 79 percent, 8 = 80 to 89 

percent, 9 = 90 percent or more. 

Census Division: 0 = Alaska and Hawaii; 1 = New England; 2 = Middle Atlantic; 3 = East North Central; 4 = West North Central; 5 = South 

Atlantic; 6 = East South Central; 7 = West South Central; 8 = Mountain; 9 = Pacific (excluding Alaska and Hawaii). 

Census Region: 1=Northeast, 2=Midwest, 3=South, 4=West. 

Median Home Value: 0 = below the 10th percentile in sample, 1 = 10th to 19th percentile in sample, 2 = 20th to 29th percentile in sample, 3 = 30th to 

39th percentile in sample, 4 = 40th to 49th percentile in sample, 5 = 50th to 59th percentile in sample, 6 = 60th to 69th percentile in sample, 7 = 70th 

to 79th percentile in sample, 8 = 80th to 89th percentile in sample, 9 = 90th percentile in sample or higher. 

MSA Status: 1 = in county in central city, 2 = in county not in central city, 3 = subcounty of MSA, 4 = MSA is its own county, 5 = non-MSA. 

SOURCE: U.S. Department of Education, National Center for Education Statistics, National Household Education Surveys Program (NHES), 2005. 
10 

were inability to make contact with the parent/guardian (36.0 percent of nonresponse), language problems 

(2.9 percent of nonresponse), and other miscellaneous reasons (13.2 percent of nonresponse) such as the 

parent/guardian being unavailable for an interview during the field period. 

The ASPA Survey had a unit response rate of 84 percent with an overall unit response rate of 

56 percent (the product of the Screener unit response rate, 67 percent, and the ASPA unit response rate, 

84 percent). The main reason for ASPA interview nonresponse was the refusal of the parent/guardian to 

respond (50.7 percent of ASPA interview nonresponse). Other reasons for nonresponse to the ASPA 

interview were inability to make contact with the parent/guardian respondent (34.4 percent of ASPA 

interview nonresponse), language problems (3.1 percent of ASPA interview nonresponse), and other 

miscellaneous reasons for nonresponse (11.8 percent of nonresponse) such as the parent/guardian being 

unavailable for an interview during the field period. 

The estimated unit response rate for the AE interview was 71 percent and the overall unit 

response rate was 48 percent (the product of the Screener unit response rate, 67 percent, and the AE unit 

response rate, 71 percent). For the AE interview, the bulk of the nonresponse was due to refusal of the 

sampled adult to respond (53.5 percent of nonresponse). Other reasons for AE interview nonresponse 

were inability to make contact with the sampled adult (27.8 percent of nonresponse), language problems 

with the sampled adult (4.8 percent of nonresponse), and other miscellaneous reasons (13.9 percent of 

nonresponse) such as the sampled adult being unable to respond due to illness. 

2.2 Analysis of Characteristics Associated with Unit Response 

Propensities 

Unit nonresponse bias may be mitigated through statistical adjustments that take advantage 

of relationships between auxiliary variables and the probability of response. (See, for example, Little 

1986; and Kalton and Flores-Cervantes 2003.) To identify characteristics associated with unit 

nonresponse, a multivariate analysis was done using a categorical search algorithm called Chi-Square 

Automatic Interaction Detection (CHAID). CHAID begins by identifying the characteristic of the data 

that is the best predictor of response. Then, within the levels of that characteristic, CHAID identifies the 

next best predictor(s) of response, and so forth, until a tree is formed with all of the response predictors 

that were identified at each step. The final result is a division of the entire data set into cells by attempting 

to determine sequentially the cells that have the greatest discrimination with respect to the unit response 
11 

rates. In other words, it divides the data set into groups so that the unit response rate within cells is as 

constant as possible, and the unit response rate between cells is as different as possible. It is important to 

note that the variables considered for use as predictors of response must be available for both respondents 

and nonrespondents. 

For Screener nonresponse adjustment, the only variables available for both respondents and 

nonrespondents were variables available on the RDD sampling frame (which were primarily demographic 

and socioeconomic characteristics of the telephone exchange) and paradata items associated with the data 

collection effort. Ten variables were identified by CHAID and used for Screener nonresponse adjustment, 

including the mailable7

 status of the telephone number; the number of answering machine messages left; 

and the following characteristics of the telephone exchange: percent White, Census division, percent 

Hispanic, Census region, median home value, percent with income $75,000 or higher, percent 

homeowners, and metropolitan statistical area (MSA) status.8

 The final Screener nonresponse adjustment 

cells and their category codes, as well as the Screener unit response rate for these cells, are shown in 

table 1. Category codes are described in the table notes. These unit response rates vary among adjustment 

cells from a low of 39 percent to a high of 100 percent. That is, Screener responses were obtained for an 

estimated 39 percent of households for which an address match can be obtained but postmaster returns are 

received when mailings are sent (cell 35). In contrast, Screener responses were obtained for an estimated 

100 percent of households for which a valid address match can be obtained, at which 3 or 4 answering 

machine messages were left, in telephone exchanges with less than 10 percent Hispanic, where the area is 

non-MSA or the MSA is its own county (cell 29). 

For ECPP and ASPA, variables considered for nonresponse adjustment included a 

combination of age and grade, whether or not the child was home schooled, Census region, and 

urbanicity. Most of these items were not available for consideration in nonresponse adjustment until after 

the Screener was completed. Based on results from the CHAID analysis, a combination of age and grade 

was used to adjust for nonresponse using the following categories: 0 year olds, 1 year olds, 2 year olds, 3 

through 6 year olds who were unenrolled, 3 through 6 year olds enrolled in preschool, kindergartners, and 

each single grade for grades 1 through 8. The ECPP and ASPA nonresponse adjustment cells, with their 

unit response rates, are given in tables 2 and 3, respectively. For ECPP, the unit response rates vary 

 

7

 “Mailable” means a valid mailing address could be matched to the sampled telephone number. 

8

 In addition to the variables identified by CHAID for use in Screener nonresponse adjustment, the following variables were also considered: 

percentage Black in the telephone exchange, percentage high school graduates in the telephone exchange, and percentage renters in the telephone 

exchange. 
12 

among adjustment cells from 83 percent to 86 percent, and for ASPA, the unit response rates also range 

from 83 percent to 86 percent. 

For AE, four variables were identified by CHAID and used for nonresponse adjustment: 

whether the respondent was also the Screener respondent, educational attainment of the adult as reported 

by the Screener respondent, adult education participation as reported by the Screener respondent, and sex 

of the adult (see table 4). Also included in the CHAID analysis but not used for nonresponse adjustment 

were Census region and urbanicity. As with ECPP and ASPA, most of these items were not available 

until after the Screener was completed. For AE, the unit response rates vary among adjustment cells from 

48 percent to 89 percent. 

2.3. A Comparison of Estimates Based on Adjusted and 

Unadjusted Weights 

One way of examining the magnitude of unit nonresponse bias and the likely effectiveness 

of statistical adjustments in reducing that bias is to compare estimates computed using adjusted weights to 

those computed using unadjusted weights. The unadjusted weight is the reciprocal of the probability of 

selection, reflecting all stages of selection. The adjusted weight is the extended interview weight adjusted 

for unit nonresponse (without the raking adjustment). It should be noted that the final raking adjustment 

also reduces nonresponse bias but is omitted from this analysis9

. In this analysis, the statistical 

significance of differences in estimates was investigated only for those differences having practical 

significance; in this case, differences of at least 3 percentage points were judged to be of practical 

significance, since effects other than unit nonresponse bias may contribute in part to the differences in the 

estimates. 

 

9

 Although raking adjustments were done on the nonresponse adjusted weights, those types of adjustments also adjust for undercoverage in 

addition to nonresponse. For that reason, the comparison of unadjusted and adjusted estimates when assessing for nonresponse bias would be 

contaminated by using the raked weights. 
13 

Table 2. ECPP interview nonresponse adjustment cells:2005 

Explanatory variables1

Number of 

respondents in 

cell

Weighted unit 

response rate 

(percent)2

Age 0 ........................................................................................ 1,036 82.9

Age 1 ........................................................................................ 1,176 84.4

Age 2 ........................................................................................ 1,386 85.9

Unenrolled (ages 3 through 6) ................................................ 1,482 83.5

Nursery school/prekindergarten .............................................. 2,126 84.7

1 Variables include age or grade/equivalent from the Screener. 

2 The unit response rate is the number of completed interviews divided by the sum of the number of 

completed interviews and nonresponses, weighted for the probability of selection but not adjusted for 

nonresponse. 

SOURCE: U.S. Department of Education, National Center for Education Statistics, Early Childhood 

Program Participation Survey (ECPP) of the National Household Education Surveys Program (NHES), 

2005. 

Table 3. ASPA interview nonresponse adjustment cells: 2005 

Explanatory variables1 Number of 

respondents in cell 

Weighted unit 

response rate 

(percent)2

Kindergarten/transitional kindergarten/pre-1st grade ................... 1,110 82.6

1st grade or equivalent .................................................................. 1,081 86.4

2nd grade or equivalent ................................................................. 1,026 84.4

3rd grade or equivalent ................................................................. 1,066 84.8

4th grade or equivalent .................................................................. 1,148 83.1

5th grade or equivalent .................................................................. 1,142 84.1

6th grade or equivalent .................................................................. 1,702 83.5

7th grade or equivalent .................................................................. 1,686 84.1

8th grade or equivalent .................................................................. 1,726 84.6

1 Variables include age or grade/equivalent from the Screener. 

2 The unit response rate is the number of completed interviews divided by the sum of the number of 

completed interviews and nonresponses, weighted for the probability of selection but not adjusted for 

nonresponse. 

SOURCE: U.S. Department of Education, National Center for Education Statistics, After School 

Programs and Activities Survey (ASPA) of the National Household Education Surveys Program (NHES), 

2005. 
14 

Table 4. AE interview nonresponse adjustment cells: 2005 

Explanatory variables1 Number of 

respondents in cell 

Weighted unit 

response rate 

(percent)2

Screener respondent/high school diploma/adult education 

participant/female ....................................................................................... 1,717 88.7 

Screener respondent/high school diploma/adult education 

participant/male .......................................................................................... 797 85.3 

Screener respondent/high school diploma/adult education 

nonparticipant/female ................................................................................. 1,679 84.5 

Screener respondent/high school diploma/adult education 

nonparticipant/male .................................................................................... 933 83.3 

Screener respondent/no high school diploma/adult education 

participant/female ....................................................................................... 131 88.7 

Screener respondent/no high school diploma/adult education 

participant/male .......................................................................................... 55 85.2 

Screener respondent/no high school diploma/adult education 

nonparticipant/female ................................................................................. 533 75.8 

Screener respondent/no high school diploma/adult education 

nonparticipant/male .................................................................................... 289 76.9 

Not Screener respondent/high school diploma/adult education 

participant/female ....................................................................................... 601 64.1 

Not Screener respondent/high school diploma/adult education 

participant/male .......................................................................................... 714 60.6 

Not Screener respondent/high school diploma/adult education 

nonparticipant/female ................................................................................. 374 58.2 

Not Screener respondent/high school diploma/adult education 

nonparticipant/male .................................................................................... 568 53.0 

Not Screener respondent/no high school diploma3 ........................................ 513 48.4 

1 Variables include an indicator of whether sampled adult was the Screener respondent, an indicator of whether 

sampled adult has a high school diploma (from Screener), adult education participation status (from the Screener), 

and sex 

2 The unit response rate is the number of completed interviews divided by the sum of the number of completed 

interviews and nonresponses, weighted for the probability of selection but not adjusted for nonresponse. 3 For this adjustment cell, adult education participation status (Screener) and sex were collapsed due to large 

adjustment factors for the original cells. 

SOURCE: U.S. Department of Education, National Center for Education Statistics, Adult Education Survey (AE) of 

the National Household Education Surveys Program (NHES), 2005. 
15 

2.3.1 Estimates of Characteristics for the ECPP and ASPA Interviews 

In order to determine the effects of the unit nonresponse adjustment on the ECPP and ASPA 

components of NHES: 2005, several characteristics of the child and of the child’s family were examined 

in a comparison of estimates constructed using the unit nonresponse-adjusted weights and the unadjusted 

weights (tables 5 and 6). In addition to these, estimates of the child’s development and care and of the 

child’s school were computed by race/ethnicity of the child separately for ECPP and ASPA, using the 

nonresponse-adjusted weights and the unadjusted weights (tables 7 and 8). Separate estimates for 

subgroups formed by race/ethnicity were considered in this analysis because they are key analytic 

subgroups. No measurable differences were observed in these comparisons of estimates. The fact that 

there were no measurable differences suggests that none of these variables were powerful predictors of 

unit response propensity. Therefore, the unit nonresponse adjustment had little effect on the potential bias, 

but it is possible that there was little to be removed. Even though grade did not differ between the 

nonresponse-adjusted and unadjusted estimates, it was used for unit nonresponse adjustment because of 

its high correlation with characteristics of the child’s after-school care and program participation. Also, 

important analytic subgroups are formed using grade. 

2.3.2 Estimates of Characteristics for the AE Interview 

In order to determine the effects of the unit nonresponse adjustment on the estimates from 

the Adult Education Survey of NHES:2005, estimates of several characteristics of adults were examined 

in a comparison of estimates based on the unit nonresponse-adjusted weights and the unadjusted weights 

(table 9). In addition to these, nonresponse-adjusted and unadjusted estimates of overall adult education 

participation and participation in each type of adult education were compared, overall and by educational 

attainment, sex, and race/ethnicity (tables 10, 11, and 12). Separate estimates for subgroups formed by 

these variables were considered in this analysis because they are key analytic subgroups. No significant 

differences were found between estimates using the two different weights, with the exception of the 

estimates of sex. Differential response between males and females is typical in NHES, so to reduce bias, 

sex (as reported by the Screener respondent) was used in unit nonresponse adjustment for the AE Survey. 
16 

Table 5. ECPP comparison of estimates based on nonresponse-adjusted weights and unadjusted 

weights for children age 0 to 6 who are enrolled in preschool or not enrolled, by child and 

family characteristics: 2005 

Nonresponse-adjusted Unadjusted Characteristic 

Percent s.e. Percent s.e.

Age/grade of child 

 Infant (age 0 to 2), unenrolled (age 3 to 6) ................. 73 0.6 73 0.5

 Nursery school/preschool/prekindergarten/Head Start 27 0.6 27 0.5

Census region1

 Northeast .................................................................... 17 0.6 18 0.8

 Midwest ...................................................................... 35 0.7 33 0.8

 South .......................................................................... 24 0.6 24 0.8

 West ........................................................................... 24 0.6 25 0.7

Race/ethnicity of child

 White, non-Hispanic ................................................... 61 0.7 60 0.7

 Black, non-Hispanic ................................................... 8 0.4 8 0.4

 Hispanic ..................................................................... 21 0.5 22 0.5

 Other3 .......................................................................... 10 0.5 10 0.5

Sex of child

 Male ........................................................................... 52 0.6 52 0.6

 Female ........................................................................ 48 0.6 48 0.6

Mother’s employment status2

 Employed ................................................................... 54 0.8 54 0.9

 Unemployed ................................................................ 44 0.8 45 0.8

 Retired/disabled or unable to work ............................ # † # †

 No mother present ...................................................... 2 0.2 2 0.2

Mother’s home language 

 English ....................................................................... 85 0.6 85 0.6

 Not English ................................................................ 14 0.5 14 0.5

 No mother present ...................................................... 2 0.2 2 0.2

Educational attainment of mother 

 Less than a high school diploma or its equivalent ...... 13 0.6 13 0.6

 High school diploma or its equivalent ........................ 22 0.7 22 0.7

 Vocational education or some college ........................ 19 0.6 19 0.6

 College degree ............................................................ 31 0.8 31 0.8

 Graduate/professional training or degree ................... 14 0.7 14 0.7

 No mother present ...................................................... 2 0.2 2 0.2

See notes at end of table. 
17 

Table 5. ECPP comparison of estimates based on nonresponse-adjusted weights and unadjusted 

weights for children age 0 to 6 who are enrolled in preschool or not enrolled, by child and 

family characteristics: 2005—Continued 

Nonresponse-adjusted Unadjusted Characteristic 

Percent s.e. Percent s.e.

 

Family type

Two parents ...................................................................................... 82 0.6 82 0.6

None or one parent ........................................................................... 18 0.6 18 0.6

 

Household income 

$5,000 or less ................................................................................... 4 0.4 4 0.4

$5,001 to $10,000 ............................................................................. 5 0.3 5 0.3

$10,001 to $15,000 ........................................................................... 5 0.4 5 0.4

$15,001 to $20,000 ........................................................................... 5 0.4 5 0.4

$20,001 to $25,000 ........................................................................... 7 0.5 7 0.5

$25,001 to $30,000 ........................................................................... 5 0.4 5 0.4

$30,001 to $35,000 ........................................................................... 5 0.4 5 0.4

$35,001 to $40,000 ........................................................................... 5 0.4 5 0.4

$40,001 to $45,000 ........................................................................... 4 0.3 4 0.3

$45,001 to $50,000 ........................................................................... 5 0.3 5 0.3

$50,001 to $60,000 ........................................................................... 9 0.5 9 0.5

$60,001 to $75,000 ........................................................................... 12 0.5 13 0.5

$75,001 to $100,000 ......................................................................... 13 0.6 13 0.6

Over $100,000 .................................................................................. 16 0.7 16 0.6

# Rounds to zero. 

† Not applicable.

1 The Northeast Census region contains Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, 

Vermont, New Jersey, New York, and Pennsylvania. The Midwest region contains Indiana, Illinois, Michigan, Ohio, 

Wisconsin, Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, and South Dakota. The South region 

contains Delaware, District of Columbia, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, 

West Virginia, Alabama, Kentucky, Mississippi, Tennessee, Arkansas, Louisiana, Oklahoma, and Texas. The West 

region contains Arizona, Colorado, Idaho, New Mexico, Montana, Utah, Nevada, Wyoming, Alaska, California, 

Hawaii, Oregon, and Washington. 

2 “Mother’s employment status” estimates exclude mothers who are not in the labor force. 3 “Other” includes children who were multiracial and not of Hispanic ethnicity, or who were American Indian or 

Alaska Natives, or were not Hispanic, White, Black, Asian, or Pacific Islander. 

NOTE: s.e. is standard error. Detail may not sum to totals because of rounding. 

SOURCE: U.S. Department of Education, National Center for Education Statistics, Early Childhood Program 

Participation Survey (ECPP) of the National Household Education Surveys Program (NHES), 2005.
18 

Table 6. ASPA comparison of estimates based on nonresponse-adjusted weights and unadjusted 

weights for children age 3 to 15 who are enrolled in kindergarten through 8th grade, by 

child and family characteristics: 2005 

Nonresponse-adjusted Unadjusted Characteristic 

Percent s.e. Percent s.e.

Grade of child 

Kindergarten .................................................................................. 12 0.4 12 0.4

1 ..................................................................................................... 11 0.3 11 0.4

2 ..................................................................................................... 10 0.3 10 0.4

3 ..................................................................................................... 11 0.4 11 0.4

4 ..................................................................................................... 11 0.4 11 0.4

5 ..................................................................................................... 11 0.3 11 0.3

6 ..................................................................................................... 12 0.3 12 0.3

7 ..................................................................................................... 11 0.3 11 0.3

8 ..................................................................................................... 12 0.3 12 0.3

 

Census region1 

Northeast ....................................................................................... 18 0.3 19 0.5

Midwest ......................................................................................... 35 0.5 33 0.7

South ............................................................................................. 24 0.5 24 0.6

West .............................................................................................. 24 0.4 25 0.6

Race/ethnicity of child 

White, non-Hispanic ...................................................................... 61 0.5 61 0.6

Black, non-Hispanic ...................................................................... 11 0.4 10 0.4

Hispanic ........................................................................................ 20 0.5 20 0.5

Other3 ............................................................................................. 9 0.3 9 0.3

Sex of child 

Male .............................................................................................. 52 0.6 52 0.6

Female ........................................................................................... 48 0.6 48 0.6

Mother’s employment status2 

Employed ...................................................................................... 62 0.6 62 0.6

Unemployed .................................................................................. 34 0.6 34 0.6

Retired/disabled or unable to work ............................................... 1 0.1 1 0.1

No mother present ......................................................................... 4 0.2 4 0.3

Mother’s home language 

English .......................................................................................... 86 0.4 85 0.3

Not English .................................................................................... 11 0.3 11 0.3

No mother present ......................................................................... 4 0.2 4 0.3

See notes at end of table. 
19 

Table 6. ASPA comparison of estimates based on nonresponse-adjusted weights and unadjusted 

weights for children age 3 to 15 who are enrolled in kindergarten through 8th grade, by 

child and family characteristics: 2005 —Continued 

Nonresponse-adjusted Unadjusted Characteristic 

Percent s.e. Percent s.e.

Educational attainment of mother 

Less than a high school diploma or its equivalent ............................ 13 0.5 13 0.5

High school diploma or its equivalent .............................................. 24 0.5 24 0.5

Vocational education or some college .............................................. 19 0.5 19 0.5

College degree .................................................................................. 29 0.6 29 0.6

Graduate/professional training or degree ......................................... 11 0.4 11 0.4

No mother present ............................................................................ 4 0.2 4 0.3

Family type 

Two parents ....................................................................................... 74 0.6 74 0.6

None or one parent ............................................................................ 26 0.6 26 0.6

Household income 

$5,000 or less ................................................................................... 3 0.3 3 0.3

$5,001 to $10,000 ............................................................................. 4 0.3 4 0.3

$10,001 to $15,000 ........................................................................... 5 0.3 5 0.3

$15,001 to $20,000 ........................................................................... 5 0.3 5 0.3

$20,001 to $25,000 ........................................................................... 7 0.3 7 0.3

$25,001 to $30,000 ........................................................................... 5 0.3 5 0.3

$30,001 to $35,000 ........................................................................... 5 0.3 5 0.3

$35,001 to $40,000 ........................................................................... 5 0.3 5 0.3

$40,001 to $45,000 ........................................................................... 3 0.2 3 0.2

$45,001 to $50,000 ........................................................................... 5 0.3 5 0.3

$50,001 to $60,000 ........................................................................... 9 0.4 9 0.4

$60,001 to $75,000 ........................................................................... 12 0.3 12 0.3

$75,001 to $100,000 ......................................................................... 13 0.4 13 0.4

Over $100,000 .................................................................................. 18 0.4 18 0.4

1 The Northeast Census region contains Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, 

Vermont, New Jersey, New York, and Pennsylvania. The Midwest region contains Indiana, Illinois, Michigan, Ohio, 

Wisconsin, Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, and South Dakota. The South region 

contains Delaware, District of Columbia, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, 

West Virginia, Alabama, Kentucky, Mississippi, Tennessee, Arkansas, Louisiana, Oklahoma, and Texas. The West 

region contains Arizona, Colorado, Idaho, New Mexico, Montana, Utah, Nevada, Wyoming, Alaska, California, 

Hawaii, Oregon, and Washington. 

2 “Mother’s employment status” estimates exclude mothers who are not in the labor force. 3 “Other” includes children who were multiracial and not of Hispanic ethnicity, or who were American Indian or 

Alaska Natives, or were not Hispanic, White, Black, Asian, or Pacific Islander. 

NOTE: s.e. is standard error. Detail may not sum to totals because of rounding. 

SOURCE: U.S. Department of Education, National Center for Education Statistics, After School Programs and 

Activities Survey (ASPA) of the National Household Education Surveys Program (NHES), 2005. 
20

Table 7. ECPP comparison of estimates of selected characteristics based on nonresponse-adjusted weights and una

children age 0 to 6 who are enrolled in preschool or not enrolled, by race/ethnicity: 2005 

Race/ethnicity Overall 

White, non-Hispanic Black, non-Hispanic Hispanic 

NR-adjusted Unadjusted NR-adjusted Unadjusted NR-adjusted Unadjusted NR-adjusted Unadjusted 

Characteristic 

Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. 

Child receiving relative care 

Yes 22 0.6 22 0.6 21 0.9 21 0.8 27 2.5 27 2.5 22 1.0 22 1.0 No 78 0.6 78 0.6 79 0.9 79 0.8 73 2.5 73 2.5 78 1.0 78 1.0 

Child receiving non-relative care 

Yes 15 0.6 15 0.5 17 0.8 17 0.8 10 1.3 10 1.3 11 1.1 11 1.1 No 85 0.6 85 0.5 83 0.8 83 0.8 90 1.3 90 1.3 89 1.1 89 1.1 

Child receiving center-based care 

Yes 38 0.7 38 0.6 41 0.9 41 0.9 46 2.6 46 2.6 27 1.3 28 1.3 No 62 0.7 62 0.6 59 0.9 59 0.9 54 2.6 54 2.6 73 1.3 72 1.3 

Child developmentally delayed 

Yes 1 0.3 1 0.3 1 0.4 1 0.4 2 1.2 2 1.2 1 0.6 1 0.6 No 99 0.3 99 0.3 99 0.4 99 0.4 98 1.2 98 1.2 99 0.6 99 0.6 

Child has specific learning disability 

Yes 2 0.3 2 0.3 2 0.4 2 0.4 4 1.3 4 1.3 2 0.6 2 0.6 No 98 0.3 98 0.3 98 0.4 98 0.4 96 1.3 96 1.3 98 0.6 98 0.6 

Child has other health impairment 

Yes 4 0.3 4 0.3 4 0.4 4 0.4 3 1.0 3 1.0 3 0.5 3 0.5 No 96 0.3 96 0.3 96 0.4 96 0.4 97 1.0 97 1.0 97 0.5 97 0.5 

See notes at end of table. 
21

Table 7. ECPP comparison of estimates of selected characteristics based on nonresponse-adjusted weights and una

children age 0 to 6 who are enrolled in preschool or not enrolled, by race/ethnicity: 2005 —Continued 

Race/ethnicity Overall 

White, non-Hispanic Black, non-Hispanic Hispanic 

NR-adjusted Unadjusted NR-adjusted Unadjusted NR-adjusted Unadjusted NR-adjusted Unadjusted 

Characteristic 

Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. 

Child has good choices for child care/early childhood pgms 

Yes 65 0.8 65 0.8 70 1.0 70 1.0 60 2.8 60 2.8 52 1.6 52 1.6 No 20 0.6 20 0.8 17 0.8 17 0.8 28 2.6 28 2.7 25 1.4 25 1.4 Have not tried to find care 15 0.6 15 0.7 12 0.8 12 0.8 12 1.6 12 1.6 24 1.3 24 1.3 

Number of times child read to in past week 

Not at all 6 0.3 5 0.3 3 0.4 3 0.4 6 1.4 6 1.4 12 1.1 12 1.1 Once or twice 14 0.5 14 0.5 10 0.6 10 0.6 18 1.6 18 1.6 22 1.4 22 1.4 3 or more times 23 0.6 23 0.6 22 0.9 22 0.9 28 2.2 28 2.2 24 1.3 24 1.3 Every day 58 0.8 58 0.8 64 1.0 65 1.0 48 2.3 48 2.3 42 1.7 42 1.7 

Someone in family taught child letters, words, or numbers 

Yes 95 0.4 95 0.4 94 0.6 94 0.6 96 1.1 96 1.1 94 0.9 94 0.9 No 5 0.4 5 0.4 6 0.6 6 0.6 4 1.1 4 1.1 6 0.9 6 0.9 

Child recognizes letters of alphabet 

All letters 22 0.6 22 0.6 24 1.0 24 1.0 21 2.3 21 2.4 12 1.3 12 1.3 Most letters 23 0.8 22 0.8 24 1.2 24 1.2 26 2.6 26 2.6 17 1.3 17 1.3 Some letters 38 0.8 38 0.9 37 1.1 37 1.1 37 2.8 37 2.7 44 1.7 44 1.7 No letters 18 0.6 18 0.7 15 1.0 15 1.0 16 2.2 16 2.2 27 1.6 27 1.6 

See notes at end of table. 
22

Table 7. ECPP comparison of estimates of selected characteristics based on nonresponse-adjusted weights and una

children age 0 to 6 who are enrolled in preschool or not enrolled, by race/ethnicity: 2005—Continued 

Race/ethnicity Overall 

White, non-Hispanic Black, non-Hispanic Hispanic 

NR-adjusted Unadjusted NR-adjusted Unadjusted NR-adjusted Unadjusted NR-adjusted Unadjusted N

Characteristic 

Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Pe

Child can write own name 

Yes 44 0.9 44 0.9 45 1.2 45 1.2 44 3.2 45 3.2 38 1.9 38 1.9 No 56 0.9 56 0.9 55 1.2 55 1.2 56 3.2 55 3.2 62 1.9 62 1.9 

† Not applicable. # Rounds to zero. 1 “Other race/ethnicity” includes children who were multiracial and not of Hispanic ethnicity, or who were American Indian or Alaska Natives, or were not Hispanic

Islander. NOTE: NR-adjusted is nonresponse-adjusted. s.e. is standard error. Detail may not sum to totals because of rounding. 

SOURCE: U.S. Department of Education, National Center for Education Statistics, Early Childhood Program Participation Survey (ECPP) of the National Household Edu

2005. 
23

Table 8. ASPA comparison of estimates of selected characteristics based on nonresponse-adjusted weights and una

children age 3 to 15 who are enrolled in kindergarten through 8th grade, by race/ethnicity: 2005 

Race/ethnicity Overall 

White, non-Hispanic Black, non-Hispanic Hispanic 

NR-adjusted Unadjusted NR-adjusted Unadjusted NR-adjusted Unadjusted NR-adjusted Unadjusted NR

Characteristic 

Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Per

Child receiving relative care 

Yes 15 0.4 15 0.4 13 0.5 13 0.5 22 1.7 22 1.7 15 0.9 15 0.9 No 85 0.4 85 0.4 87 0.5 87 0.5 78 1.7 78 1.7 85 0.9 85 0.9 

Child receiving non-relative care 

Yes 6 0.3 6 0.3 6 0.4 6 0.4 5 0.8 5 0.8 5 0.7 5 0.7 No 94 0.3 94 0.3 94 0.4 94 0.4 95 0.8 95 0.8 95 0.7 95 0.7 

Child receiving center-based care 

Yes 20 0.5 21 0.5 17 0.6 17 0.6 33 2.0 33 2.0 24 1.3 24 1.3 No 80 0.5 79 0.5 83 0.6 83 0.6 67 2.0 67 2.0 76 1.3 76 1.3 

Child receiving after school care 

Yes 52 0.6 52 0.6 61 0.8 61 0.8 37 1.9 37 1.9 33 1.3 33 1.3 No 48 0.6 48 0.6 39 0.8 39 0.8 63 1.9 63 1.9 67 1.3 67 1.3 

Child receiving self care 

Yes 13 0.4 13 0.4 13 0.5 13 0.5 17 1.3 17 1.2 13 0.8 13 0.8 No 87 0.4 87 0.4 87 0.5 87 0.5 83 1.3 83 1.2 87 0.8 87 0.8 

Child has specific learning disability 

Yes 7 0.3 7 0.3 7 0.4 7 0.3 9 1.0 9 1.0 6 0.5 6 0.5 No 93 0.3 93 0.3 93 0.4 93 0.3 91 1.0 91 1.0 94 0.5 94 0.5 

Child has other health impairment 

Yes 5 0.3 5 0.3 6 0.3 6 0.3 6 0.9 6 0.9 4 0.5 4 0.5 No 95 0.3 95 0.3 94 0.3 94 0.3 94 0.9 94 0.9 96 0.5 96 0.5 

See notes at end of table. 
24

Table 8. ASPA comparison of estimates of selected characteristics based on nonresponse-adjusted weights and una

children age 3 to 15 who are enrolled in kindergarten through 8th grade, by race/ethnicity: 2005—Continu

Race/ethnicity Overall 

White, non-Hispanic Black, non-Hispanic Hispanic 

NR-adjusted Unadjusted NR-adjusted Unadjusted NR-adjusted Unadjusted NR-adjusted Unadjusted 

Characteristic 

Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. Percent s.e. P

School type 

Public 88 0.4 88 0.4 86 0.6 86 0.6 90 1.1 90 1.1 93 0.7 93 0.7 Private 12 0.4 12 0.4 14 0.6 14 0.6 10 1.1 10 1.1 7 0.7 7 0.7 

Whether school assigned or chosen 

Assigned 84 0.5 84 0.5 86 0.5 86 0.5 74 1.8 74 1.8 85 0.9 84 0.9 Chosen 14 0.4 14 0.4 11 0.5 11 0.5 24 1.8 24 1.8 14 0.9 14 0.9 Assigned school is chosen 2 0.2 2 0.2 3 0.3 3 0.3 2 0.5 2 0.5 2 0.3 2 0.3 

Contact from school about child’s behavior 

Yes 16 0.4 16 0.4 14 0.5 14 0.5 28 1.7 28 1.6 16 1.0 16 1.0 No 84 0.4 84 0.4 86 0.5 86 0.5 72 1.7 72 1.6 84 1.0 84 1.0 

Child’s overall grades 

Mostly As 34 0.5 34 0.5 37 0.7 37 0.7 29 1.5 29 1.5 27 1.2 27 1.2 Mostly Bs 24 0.5 23 0.5 22 0.6 22 0.6 29 1.4 29 1.4 28 1.1 28 1.1 Mostly Cs 9 0.3 9 0.3 8 0.4 8 0.4 14 1.3 14 1.3 10 0.9 10 0.9 Mostly Ds 2 0.1 2 0.1 1 0.2 1 0.2 2 0.3 2 0.3 3 0.4 3 0.4 Mostly Fs 1 0.1 1 0.1 1 0.1 1 0.1 1 0.4 1 0.4 1 0.3 1 0.3 No grades given 31 0.5 32 0.5 32 0.7 32 0.7 25 1.4 25 1.4 31 1.3 32 1.3 

Contact from school about child’s school work 

Yes 21 0.5 21 0.5 19 0.6 20 0.6 26 1.4 26 1.4 23 1.1 23 1.1 No 79 0.5 79 0.5 81 0.6 81 0.6 74 1.4 74 1.4 77 1.1 77 1.1 

† Not applicable. # Rounds to zero. 1 “Other race/ethnicity” includes children who were multiracial and not of Hispanic ethnicity, or who were American Indian or Alaska Natives, or were not Hispanic

Islander. NOTE: NR-adjusted is nonresponse-adjusted. s.e. is standard error. Detail may not sum to totals because of rounding. 

SOURCE: U.S. Department of Education, National Center for Education Statistics, After School Programs and Activities Survey (ASPA) of the National Household Edu

2005. 
25 

Table 9. AE comparison of estimates based on nonresponse-adjusted weights and unadjusted 

weights for adults, by demographic characteristics: 2005 

Nonresponse-adjusted Unadjusted Characteristic 

Percent s.e. Percent s.e.

Census region1 

Northeast ........................................................... 18 0.5 19 0.6

Midwest ............................................................. 36 0.8 34 0.8

South ................................................................. 24 0.7 24 0.6

West .................................................................. 23 0.7 23 0.7

Educational attainment 

Less than a high school diploma or its equivalent 11 0.4 10 0.4

High school diploma or its equivalent and/or some 

college, associate’s degree, or voc/tech 

school ............................................................. 56 0.8 56 0.8

Bachelor’s degree or higher .............................. 33 0.8 34 0.7

Household income 

$5,000 or less .................................................... 3 0.2 3 0.2

$5,001 to $10,000 .............................................. 4 0.3 4 0.3

$10,001 to $15,000 ............................................ 5 0.3 5 0.3

$15,001 to $20,000 ............................................ 5 0.3 5 0.3

$20,001 to $25,000 ............................................ 6 0.4 6 0.4

$25,001 to $30,000 ............................................ 5 0.3 5 0.3

$30,001 to $35,000 ............................................ 5 0.3 5 0.3

$35,001 to $40,000 ............................................ 5 0.4 5 0.4

$40,001 to $50,000 ............................................ 4 0.2 4 0.2

$50,001 to $75,000 ............................................ 5 0.4 5 0.4

Over $75,000 ..................................................... 10 0.5 10 0.5

Race/ethnicity 

White, non-Hispanic .......................................... 75 0.7 75 0.7

Black, non-Hispanic .......................................... 7 0.3 7 0.3

Hispanic ............................................................ 11 0.5 10 0.4

Other6 ................................................................. 7 0.5 7 0.5

Sex 

Male .................................................................. 48 0.6 44 0.7

Female ............................................................... 52 0.6 56 0.7

See notes at end of table. 
26 

Table 9. AE comparison of estimates based on nonresponse-adjusted weights and unadjusted 

weights for adults, by demographic characteristics: 2005—Continued 

Nonresponse-adjusted Unadjusted Characteristic 

Percent s.e. Percent s.e.

Type of adult education activity 

Any adult education activity2 ............................. 45 0.7 46 0.7

Any ABE/GED3,4 ............................................... 1 0.2 1 0.1

Any ESL5 ........................................................... 5 0.7 5 0.7

Any credential programs2 .................................. 11 0.5 11 0.5

Any apprenticeship program ............................. 1 0.2 1 0.1

Any work-related course ................................... 29 0.7 29 0.6

Any personal development course ..................... 22 0.7 23 0.6

Any vocational/technical course ....................... 2 0.2 2 0.2

Any distance learning course ............................ 31 1.0 32 0.9

Any informal learning course ............................ 72 0.8 73 0.8

1 The Northeast Census region contains Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, 

Vermont, New Jersey, New York, and Pennsylvania. The Midwest region contains Indiana, Illinois, Michigan, Ohio, 

Wisconsin, Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, and South Dakota. The South region 

contains Delaware, District of Columbia, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, 

West Virginia, Alabama, Kentucky, Mississippi, Tennessee, Arkansas, Louisiana, Oklahoma, and Texas. The West 

region contains Arizona, Colorado, Idaho, New Mexico, Montana, Utah, Nevada, Wyoming, Alaska, California, 

Hawaii, Oregon, and Washington. 

2 Adults who participated in a credential program on a full-time basis only, for part or all of the year, and did not 

participate in any other type of formal educational activity are not counted as participants in adult education. Adults 

who participated in a credential program on a full-time basis only and also participated in another type of adult 

education are included in the overall rate and the rate for the type of noncredential adult education in which they 

participated, but not in the credential program rate. Adults who participated in a credential program on a part-time 

basis only or on both part-time and full-time basis are included in the credential rate and the overall rate. 3 Adult basic education/general education development (ABE/GED). Respondents who did not have a high school 

diploma or its equivalent, received a high school diploma or its equivalent in the past 12 months, or received a high 

school diploma in a foreign country were asked about participation in adult basic education, GED preparation 

classes, adult high school equivalency programs. 

4 Persons with a bachelor’s degree or more education were not asked about participation in adult basic education, 

GED preparation classes, adult high school, or high school equivalency programs. 

5 Respondents whose primary language is other than English were asked about participation in English as a second 

language classes. 

6 “Other” includes children who were multiracial and not of Hispanic ethnicity, or who were American Indian or 

Alaska Natives, or were not Hispanic, White, Black, Asian, or Pacific Islander. 

NOTE: s.e. is standard error. Detail may not sum to totals because of rounding. 

SOURCE: U.S. Department of Education, National Center for Education Statistics, Adult Education Survey (AE) of 

the National Household Education Surveys Program (NHES), 2005.
27

Table 10. AE comparison of estimates based on nonresponse-adjusted and unadjusted weights for adults who took 

education activities in a 12-month period, by race/ethnicity: 2005 

Race/ethnicity 

White, non-Hispanic Black, n

Nonresponse-adjusted Unadjusted Nonresponse-adjusted 

Type of adult education activity 

Percent s.e. Percent s.e. Percent s.e

Any adult education activity1 ............................................ 47 0.9 48 0.8 46 2.

Any ABE/GED2,3 .............................................................. 1 0.1 1 0.1 1 0.

Any ESL4 .......................................................................... 4 1.2 3 1.2 # 

Any credential programs1 ................................................. 10 0.6 10 0.5 11 1.

Any apprenticeship program ............................................ 1 0.2 1 0.1 1 0.

Any work-related course .................................................. 31 0.8 31 0.7 28 2.Any personal development course .................................... 23 0.9 24 0.8 24 2.Any vocational/technical course ....................................... 1 0.2 1 0.2 2 0.Any distance learning course ............................................ 30 1.1 31 1.1 35 3.

Any informal learning course ........................................... 74 0.9 75 0.8 67 2.

See notes at end of table. 
28

Table 10. AE comparison of estimates based on nonresponse-adjusted and unadjusted weights for adults who took 

education activities in a 12-month period, by race/ethnicity: 2005—Continued 

Race/ethnicity

Hispanic O

Nonresponse-adjusted Unadjusted Nonresponse-adjusted 

Type of adult education activity 

Percent s.e. Percent s.e. Percent s.e

Any adult education activity1 ............................................ 37 2.2 38 2.1 43 2.

Any ABE/GED2,3 .............................................................. 7 1.0 7 0.9 1 0.

Any ESL4 .......................................................................... 7 1.1 7 1.0 3 1.

Any credential programs1 ................................................. 10 1.3 11 1.3 18 3.

Any apprenticeship program ............................................ 2 0.8 2 0.6 1 0.

Any work-related course .................................................. 17 1.7 19 1.6 24 2.Any personal development course .................................... 16 1.5 17 1.4 22 2.Any vocational/technical course ....................................... 2 0.6 2 0.5 2 0.Any distance learning course ............................................ 30 3.3 31 3.1 41 4.

Any informal learning course ........................................... 58 2.6 59 2.6 78 2.

† Not applicable. # Rounds to zero. 1 Adults who participated in a credential program on a full-time basis only, for part or all of the year, and did not participate in an

educational activity are not counted as participants in adult education. Adults who participated in a credential program on a full-tim

participated in another type of adult education are included in the overall rate and the rate for the type of noncredential adult education in but not in the credential program rate. Adults who participated in a credential program on a part-time basis only or on both part-time included in the credential rate and the overall rate. 

2 Adult basic education/general education development (ABE/GED). Respondents who did not have a high school diploma or its equ

school diploma or its equivalent in the past 12 months, or received a high school diploma in a foreign country were asked about part

education, GED preparation classes, and adult high school equivalency programs. 

3 Persons with a bachelor’s degree or more education were not asked about participation in adult basic education, GED preparation classes

adult high school equivalency programs. 

4 Respondents whose primary language is other than English were asked about participation in English as a second language classes. 

NOTE: s.e. is standard error. Percents for different types of adult education sum to more than the overall participation rate because so

more than one type of activity or program. 

5 “Other” includes children who were multiracial and not of Hispanic ethnicity, or who were American Indian or Alaska Natives, or we

Black, Asian, or Pacific Islander. SOURCE: U.S. Department of Education, National Center for Education Statistics, Adult Education Survey (AE) of the National HousehProgram (NHES), 2005.
29

Table 11. AE comparison of estimates based on nonresponse-adjusted and unadjusted weights for adults who took 

education activities in a 12-month period, by sex: 2005 

Sex 

Male Femal

Nonresponse-adjusted Unadjusted Nonresponse-adjusted 

Type of adult education activity 

Percent s.e. Percent s.e. Percent s.e. 

Any adult education activity1 .............................. 42 1.1 43 1.1 51 1.0 

Any ABE/GED2,3 ................................................ 1 0.3 1 0.2 2 0.2 

Any ESL4 ............................................................ 4 1.0 4 1.0 6 0.9 

Any credential programs1 ................................... 10 0.6 10 0.6 12 0.7 

Any apprenticeship program .............................. 2 0.3 1 0.3 1 0.1 Any work-related course .................................... 26 1.0 27 0.9 31 1.0 Any personal development course ...................... 19 1.0 19 1.0 25 0.9 Any vocational/technical course ......................... 2 0.3 2 0.3 1 0.2 

Any distance learning course .............................. 34 1.8 35 1.8 29 1.4 Any informal learning course ............................. 72 1.1 73 1.0 72 1.0 

1 Adults who participated in a credential program on a full-time basis only, for part or all of the year, and did not participate in an

educational activity are not counted as participants in adult education. Adults who participated in a credential program on a full-tim

participated in another type of adult education are included in the overall rate and the rate for the type of noncredential adult education in but not in the credential program rate. Adults who participated in a credential program on a part-time basis only or on both part-time included in the credential rate and the overall rate. 

2 Adult basic education/general education development (ABE/GED). Respondents who did not have a high school diploma or its equ

school diploma or its equivalent in the past 12 months, or received a high school diploma in a foreign country were asked about part

education, GED preparation classes, and adult high school equivalency programs. 

3 Persons with a bachelor’s degree or more education were not asked about participation in adult basic education, GED preparation classes

adult high school equivalency programs. 

4 Respondents whose primary language is other than English were asked about participation in English as a second language classes. 

NOTE: s.e. is standard error. Percents for different types of adult education sum to more than the overall participation rate because some athan one type of activity or program. SOURCE: U.S. Department of Education, National Center for Education Statistics, Adult Education Survey (AE) of the National HouseProgram (NHES), 2005.
30

Table 12. AE comparison of estimates based on nonresponse-adjusted and unadjusted weights for adults who took 

education activities in a 12-month period, by educational achievement:2005 

Educational attainment 

Less than a high school diploma or its equivalent High school diploma or its eq

associate’s degree, or vocat

Nonresponse-adjusted Unadjusted Nonresponse-adjusted 

Type of adult education activity 

Percent s.e. Percent s.e. Percent s.e. 

Any adult education activity1 ........... 20 1.4 20 1.3 40 0.9 

Any ABE/GED2,3 ............................. 7 1.0 7 0.8 1 0.2 

Any ESL4 ......................................... 6 1.4 6 1.4 6 1.2 

Any credential programs1 ................ 2 0.4 1 0.4 13 0.8 

Any apprenticeship program ........... 1 0.2 1 0.2 1 0.2 

Any work-related course ................. 4 0.6 4 0.6 23 0.8 

Any personal development course ... 11 1.1 11 1.1 20 0.9 

Any vocational/technical course ...... 1 0.4 1 0.3 2 0.2 

Any distance learning course ........... 21 3.4 23 3.4 32 1.4 

Any informal learning course .......... 46 1.9 46 1.8 71 1.2 

See notes at end of table. 
31

Table 12. AE comparison of estimates based on nonresponse-adjusted and unadjusted weights for adults who took 

education activities in a 12-month period, by educational achievement: 2005 —Continued 

Educational attainment 

Bachelor’s degree or higher 

Nonresponse-adjusted Unadjust

Type of adult education activity 

Percent s.e. Percent 

Any adult education activity1 .............. 62 1.3 63 

Any ABE/GED2,3 ................................ # † # 

Any ESL4 ............................................ 3 1.2 3 

Any credential programs1 ................... 11 0.7 12 

Any apprenticeship program .............. 1 0.3 1 

Any work-related course .................... 46 1.4 46 Any personal development course ...... 30 1.2 31 Any vocational/technical course ........ 1 0.2 1 Any distance learning course ............. 32 1.6 32 Any informal learning course ............ 83 1.1 84 

† Not applicable. # Rounds to zero. 1 Adults who participated in a credential program on a full-time basis only, for part or all of the year, and did not participate in any other 

activity are not counted as participants in adult education. Adults who participated in a credential program on a full-time basis only and 

type of adult education are included in the overall rate and the rate for the type of noncredential adult education in which they participateprogram rate. Adults who participated in a credential program on a part-time basis only or on both part-time and full-time basis are include

the overall rate. 

2 Adult basic education/general education development (ABE/GED). Respondents who did not have a high school diploma or its equival

diploma or its equivalent in the past 12 months, or received a high school diploma in a foreign country were asked about participation in 

preparation classes, and adult high school equivalency programs. 

3 Persons with a bachelor’s degree or more education were not asked about participation in adult basic education, GED preparation clas

adult high school equivalency programs. 

4 Respondents whose primary language is other than English were asked about participation in English as a second language classes. 

NOTE: s.e. is standard error. Percents for different types of adult education sum to more than the overall participation rate because somthan one type of activity or program. SOURCE: U.S. Department of Education, National Center for Education Statistics, Adult Education Survey (AE) of the National HouProgram (NHES), 2005. 
32 

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33 

3. Item Nonresponse Bias 

In the ECPP, ASPA, and AE Surveys, as in most surveys, the responses to some data items 

are not obtained for all interviews. There are numerous reasons for item nonresponse. Some respondents 

do not know the answer for the item or do not wish to respond for other reasons. Some item nonresponse 

arises when an interview is interrupted and not continued later, leaving items at the end of the interview 

blank. Item nonresponse may also be encountered because responses provided by the respondent are not 

internally consistent, and this inconsistency is not discovered until after the interview is completed. In 

such cases, the items that were not internally consistent were set to missing. This section contains an 

evaluation of the potential for bias due to item nonresponse. In many surveys, such an evaluation would 

contain an examination of differences between item respondents and the full sample in characteristics 

available on the sampling frame. However, in RDD samples, the sampling frame data are limited to 

general characteristics of the telephone exchange, which only cover a small percentage of items in the 

survey. Also, for the items in the survey that do match frame data, there is the temporal consideration that 

these characteristics pertained at the time of the 2000 decennial census. 

Section 3.1 gives item response rates for the three surveys, and describes the items that are 

included in the item nonresponse bias analysis. For the ECPP, ASPA, and AE surveys, the median item 

response rates were 99.3 percent, 99.2 percent, and 98.8 percent, respectively, and the median total 

response rates (the product of the item response rates and overall unit response rates) were 56.0 percent, 

55.8 percent, and 47.0 percent, respectively. With such high item response rates, there is little potential 

for item nonresponse bias for most items. However, because there is the potential for item nonresponse 

bias in estimates involving items with lower item response rates, this analysis focuses on those items. 

Because complete data were needed for variables used in weighting and because having 

complete data will facilitate analyses, numeric and categorical data items with missing data on the file 

were imputed. (In general, character string variables, such as countries of origin, languages, or 

“other/specify” responses were not imputed.10) A hot-deck procedure was used to impute most missing 

 

10 The exceptions were some character string variables in the AE interview (e.g., major field of study, industry) that were coded into new 

variables (e.g., major field of study codes, industry codes). In cases where the original string variable was missing, the string variable was 

imputed and then coded into the new variable. The restricted-use data files contain the imputed character strings and the public files contain the 

coded variables based upon these imputed strings. 
34 

responses for items.11 In this approach, the entire file was sorted into cells defined by characteristics of 

households or respondents that are likely to be associated with differences in response propensities. These 

characteristics, or boundary variables, were used to group respondents into those most likely to have the 

same response or the same response propensity for the data item to be imputed. Two types of boundary 

variables were used. Hard boundary variables were considered to be so important that the donor and the 

recipient were required to match exactly. For other boundary variables, called soft boundary variables, the 

values did not have to match exactly. In effect, the hard boundary variables were matching variables and 

the soft boundary variables were used to order the cases within the matching variables. By forming cells 

using boundary variables that are associated with the item or with its response propensity, a reduction in 

item nonresponse bias should be affected by hot-deck imputation. 

Section 3.2 contains comparisons of weighted means or frequency distributions for items 

with and without imputed values, using the final raked weights. This is similar to the analysis comparing 

adjusted and unadjusted estimates that was conducted to examine unit nonresponse bias, described in 

section 2.3. Large differences are likely to indicate a reduction in item nonresponse bias through 

imputation, and an absence of measurable differences suggests that either imputation had little effect on 

the potential bias or that there was little to be removed. 

Section 3.3 examines the potential for item nonresponse bias by imposing extreme 

assumptions on the item nonrespondents. Because item nonresponse bias may be viewed as a function of 

both the item nonresponse rate and the extent to which the item nonrespondents differ from the item 

respondents, bounds on the item nonresponse bias may be obtained by imposing extreme assumptions on 

the item nonrespondents. Extreme assumptions are created by imputing values that fall in the tails of the 

original distribution, for example, in the 5th or 95th percentiles, or by imputing equal percentages when the 

original distribution is skewed. 

 

11 For some items, the missing values were imputed manually rather than using the hot-deck procedure. In NHES:2005, manual imputation (see 

Hagedorn, et. al., forthcoming) was done (1) to impute certain person-level demographic characteristics; (2) to impute whether a child is home 

schooled, whether the child attends regular school for some classes, and the number of hours the child attends regular school; (3) to correct for a 

small number of inconsistent imputed values; and (4) to impute for a few cases when no donors with matching boundary variable values could be 

found. 
35 

3.1 Item Response Rates and Items Included in this Analysis 

As noted above, the median item response rates were 99.3 percent, 99.2 percent, and 98.8 

percent for items from the ECPP, ASPA, and AE Surveys, respectively. These median rates are very high; 

thus, for most items, even if the item nonrespondents differ considerably from the respondents, the item 

nonresponse bias will be negligible. As a result, only items having an item response rate of less than 90 

percent were considered for this item nonresponse bias analysis. The minimum item response rate in this 

analysis is 70.8 percent, for the AE variable APCLSHR (total hours of classroom instruction). For items 

that apply to only a very small number of cases, sampling error and other sources of error could have a 

much larger effect on the estimates than item nonresponse bias. Therefore, only items that applied to 30 

or more respondents were included in this analysis. Also, items for third or fourth child care arrangements 

for ECPP and ASPA, and items for third or higher educational activities for AE were not included. After 

applying these criteria, the item nonresponse bias analysis was done on three ECPP items, 15 ASPA 

items, and 31 AE items. (See tables 13, 14, and 15, respectively, for lists of these items and their item 

response rates.) 

Table 13. ECPP items included in the nonresponse bias analysis: 2005 

Variable 

Question number and description 

Number of 

respondents 

Item 

response rate 

(percent) 

Total 

response rate 

(percent)

 

RCCSTHN1 ED22OV-# OF CHILDREN AMOUNT IS FOR-1 95 89.5 50.5 

NCCOST2 EE25-AMT HH PAYS FOR NONREL CARE-2 65 89.2 50.3 

RCWKMO2 ED9-# OF WKS/MO RECEIVES REL CARE-2 64 87.5 49.4 

NOTE: Total response rate is the product of the item response rate and the overall unit response rate for ECPP. 

SOURCE: U.S. Department of Education, National Center for Education Statistics, Early Childhood Program 

Participation (ECPP) Survey of the National Household Education Surveys Program (NHES), 2005.
36 

Table 14. ASPA items included in the nonresponse bias analysis: 2005 

Variable 

Question number and description 

Number of 

respondents 

Item 

response rate 

(percent) 

Total 

response 

rate 

(percent)

 

CPCOST1 SH15-AMOUNT HH PAYS FOR PROGRAM-1 1,256 89.5 50.4 

CPCOST2 SH15-AMOUNT HH PAYS FOR PROGRAM-2 236 89.4 50.3 

CPUNIT2 SH15-UNIT OF TIME/PROGRAM COST-2 224 89.3 50.3 

CPUNIT1 SH15-UNIT OF TIME/PROGRAM COST-1 1,181 89.1 50.2 

ASWKMO SI5-# OF WKS/MO IN ACTIVITIES 301 89.0 50.1 

RCCSTHH1 SF16-AMOUNT FOR CHILD ONLY OR OTHERS-1 160 88.8 50.0 

RCCSTHN1 SF16OV-# OF CHILDREN AMOUNT IS FOR-1 77 88.3 49.7 

CPCSTHH1 SH16-AMOUNT FOR CHILD ONLY OR OTHERS-1 744 88.3 49.7 

ASDAYWK SI6-# OF DAYS/WK IN ACTIVITIES 301 88.0 49.6 

ASHRWK SI7-# OF HRS/WK IN ACTIVITIES 301 88.0 49.6 

RCWKMO1 SF10 -# OF WKS/MO RECEIVES REL CARE-1 30 86.7 48.8 

CPKIDS1 SH24-# OF CHILDREN IN GROUP AT PROGRAM-1 2,266 85.5 48.2 

SCWKMO SJ8-# OF WKS/MO IN SELF-CARE 70 81.4 45.9 

CPCSTHN1 SH16OV-# OF CHILDREN AMOUNT IS FOR-1 61 80.3 45.2 

NCCOST2 SG14-AMT HH PAYS FOR NONREL CARE-2 32 78.1 44.0 

NOTE: Total response rate is the product of the item response rate and the overall unit response rate for ASPA. 

SOURCE: U.S. Department of Education, National Center for Education Statistics, After School Programs and 

Activities (ASPA) Survey of the National Household Education Surveys Program (NHES), 2005.

Table 15. AE items included in the nonresponse bias analysis: 2005 

Variable 

Question number and description 

Number of 

respondents 

Item 

response 

rate 

(percent) 

Total 

response 

rate 

(percent) 

 

VOCOMPY1 AE7-VOCA COMPLETION YEAR-1 173 89.0 42.4 

VOENRNU1 AE9-HOW LONG ENROLLED IN PRGM-1 173 89.0 42.4 

VOENRUN1 AE9-UNIT ENROLLED IN PRGM-1 173 89.0 42.4 

CREMPRE2 AD18-EMPLOYER REQUIRED TO TAKE PRGM-2 91 89.0 42.4 

CRWRKPL2 AD20-TOOK PRGM AT WORKPLACE-2 91 89.0 42.4 

CRWRKHR2 AD21-TOOK PRGM DURING WORK HRS-2 91 89.0 42.4 

CREMPAI2 AD22-BEING PAID WHILE TAKING PRGM-2 91 89.0 42.4 

CREMPMA2 AD23B-EMPLOYER PAID BOOKS/MTLS-2 91 89.0 42.4 

CRSTRTM2 AD8-CRED START MONTH-2 117 88.9 42.3 

CRCOMPM2 AD9-CRED COMPLETION MONTH-2 117 88.0 41.9 

CREMPTU2 AD23A-EMPLOYER PAID TUITION/FEES-2 91 87.9 41.9 

APSTRTMM AF4-APPR PRGM START MONTH 89 87.6 41.7 

BSHRYR AC8-TOTAL HRS ATTENDED ABE/GED 128 87.5 41.7 

See notes at end of table. 
37 

Table 15. AE items included in the nonresponse bias analysis: 2005—Continued 

Variable 

Question number and description 

Number of 

respondents 

Item 

response 

rate 

(percent) 

Total 

response 

rate 

(percent) 

 

CRCOMPY2 AD9-CRED COMPLETION YEAR-2 117 86.3 41.1 

CRMATLS2 AD15B-PERSONAL EXPENSE FOR BKS/MTLS-2 117 86.3 41.1 

HINCMRNG PW18/AM12-TOTAL HH INCOME RANGE 8,904 86.2 41.1 

CRSTRTY2 AD8-CRED START YEAR-2 117 85.5 40.7 

CRTUITO2 AD15A-PERSONAL EXPENSE FOR TUIT/FEES-2 117 84.6 40.3 

CRTUITO2 AD15A-PERSONAL EXPENSE FOR TUIT/FEES-2 117 84.6 40.3 

APCOMPMM AF5-APPR PRGM COMPLETION MONTH 89 84.3 40.1 

APCOMPYY AF5-APPR PRGM COMPLETION YEAR 89 83.2 39.6 

HINCM50K PW19/AM120V-HH INCOME BELOW/ABOVE $50K 6,404 82.9 39.5 

CRENRNU2 AD12-HOW LONG ENROLLED IN PRGM-2 117 79.5 37.8 

CRENRUN2 AD12-UNIT ENROLLED IN PRGM-2 117 79.5 37.8 

CRCRDHR2 AD13-TOTAL CREDIT HRS ENROLLED-2 117 79.5 37.8 

HINCOME PW19/AM120V-TOTAL HH INCOME RANGE 2 8,904 78.6 37.4 

EARNAMT AL25-AMOUNT OF EARNINGS 5,940 78.6 37.4 

EARNUNT AL25-UNIT OF EARNINGS 5,940 78.6 37.4 

VOCLSHR1 AE12-TOTAL CLASSROOM HRS-1 76 72.4 34.5 

VOCRDHR1 AE11-TOTAL CREDIT HRS ENROLLED-1 173 72.3 34.4 

APCLSHR AF6-TOTAL CLASSROOM INST HRS 89 70.8 33.7 

NOTE: Total response rate is the product of the item response rate and the overall unit response rate for AE. 

SOURCE: U.S. Department of Education, National Center for Education Statistics, Adult Education (AE) Survey of 

the National Household Education Surveys Program (NHES), 2005. 

3.2 Assessment of Means or Distributions for Items With and 

Without Imputed Values 

For each item designated for nonresponse bias analysis, means (for continuous variables) or 

frequency distributions (for dichotomous and categorical variables) were estimated both with and without 

imputed values to assess the effect of imputation. Tables 16 and 17 give means and relative frequency 

distributions, respectively, for each item with and without the imputed values for the ECPP, ASPA, and 

AE Surveys. These means and relative frequency distributions were compared, and no measurable 

differences were detected between any of the means or distributions with imputed values and without 

imputed values.12 These results suggest that even for these items with response rates of less than 90 

percent, the potential for bias due to item nonresponse is minimal. 

 

12 Some apparent differences are between estimates with relatively large standard errors (over 50% of the related estimate). Interpreting results 

from statistical tests based on relatively large standard errors may not be substantively meaningful. Many estimates in tables 16 and 17 have 

large standard errors because of small sample sizes. 
38 

Table 16. Means for items with and without imputed values: 2005 

With imputed values Without imputed values Continuous variables

Mean s.e. Mean s.e. 

ECPP 

Amount household pays for non-relative care 

arrangement 2 (NCCOST2) ........................................... 116! 73.4 116! 80.9 

ASPA 

Amount household pays for center-based care 

arrangement 1 (CPCOST1) ............................................ 141 22.0 143 24.5 

Amount household pays for center-based care 

arrangement 2 (CPCOST2) ............................................ 169 33.2 139 22.4 

Number of hours per week in activity (ASHRWK) ......... 3 0.1 3 0.1 

Number of kids in center-based arrangement 1 

(CPKIDS1) ................................................................... 20 0.4 19 0.5 

Amount household pays for non-relative care 

arrangement 2 (NCCOST2) .......................................... 56! 28.9 54! 33.3 

AE 

Total hours attended ABE/GED (BSHRYR) ................... 61 11.3 56 10.5 

Personal expenses for books/materials, degree/credential 

arrangement 2 (CRMATLS2) ....................................... 372 62.5 385 64.0 

Personal expenses for tuition/fees, degree/credential 

arrangement 2 (CRTUITO2) ........................................ 3,801 866.8 4,040 1,003.5 

Total degree/credential credit hours enrolled, 

arrangement 2 (CRCRDHR2) ....................................... 22 3.2 23 3.6 

Derived earnings per year (EARNAMTYR)1 ................... 39,243 597.9 38,588 633.8 

Total vocational classroom hours, arrangement 1 

(VOCLSHR1) ............................................................... 95 14.5 97 14.9 

Total vocational credit hours enrolled, arrangement 1 

(VOCRDHR1) .............................................................. 55 4.7 54 5.8 

Total apprenticeship classroom instruction hours 

(APCLSHR) .................................................................. 62 8.3 56 6.8 

Derived total months in vocational arrangement 1 

(VOTIME1)2 ................................................................. 19 2.4 15 2.1 

Derived total months in degree/credential arrangement 2 

(CRTIME2) 2 ................................................................. 39 2.8 37 2.7 

Derived total months in apprenticeship arrangement 

(APTIME) 2 ................................................................... 22 3.6 19 4.1 

! Interpret data with caution; coefficient of variation is 50 percent or more.

1 EARNAMTYR is derived from EARNAMT and EARNUNT to create an annual earnings variable for analysis. 2 VOTIME1 is derived from VOSTRTM1, VOSTRTY1, VOCOMPM1, and VOCOMPY1 to create a total number 

of months in the first vocational program. CRTIME2 is derived similarly from CRSTRTM2, CRSTRTY2, 

CRCOMPM2, and CRCOMPY2. APTIME is derived similarly from APSTRTMM, APSTRTYY, APCOMPMM, 

and APCOMPYY. 

NOTE: s.e. is standard error. Detail may not sum to totals because of rounding. 

SOURCE: U.S. Department of Education, National Center for Education Statistics, Early Childhood Program 

Participation (ECPP) Survey of the National Household Education Surveys Program (NHES), 2005, After School 

Programs and Activities (ASPA) Survey of the National Household Education Surveys Program (NHES), 2005, and 

Adult Education (AE) Survey of the National Household Education Surveys Program (NHES), 2005. 
39 

Table 17. Relative frequency distributions for items with and without imputed values: 2005 

With imputed values Without imputed values Categorical variables Percent s.e. Percent s.e. 

 

ECPP 

Number of children relative care amount is for, 

arrangement 1 (RCCSTHN1) 

2 children ........................................................................... 86 6.0 86 5.5 

3 children ........................................................................... 5 2.0 6 2.4 

4 children ........................................................................... 9! 6.1 8! 5.4 

 

Number of weeks per month child receives relative care, 

arrangement 2 (RCWKMO2) 

1 week ............................................................................... 64 8.5 63 10.0 

2 weeks .............................................................................. 32 7.8 32 9.1 

3 weeks .............................................................................. 5! 3.5 5! 4.0 

 

ASPA 

Unit of time, center-based program cost 1 (CPUNIT1) 

Hour ................................................................................... 6 0.9 6 1.0 

Day .................................................................................... 7 0.9 6 0.9 

Week .................................................................................. 29 1.8 31 2.0 

Month ................................................................................ 41 2.2 42 2.3 

Year ................................................................................... 9 1.4 9 1.6 

Every two weeks ............................................................... 1 0.2 1 0.3 

Other .................................................................................. 7 1.6 5 1.0 

 

Unit of time, center-based program cost 2 (CPUNIT2) 

Hour ................................................................................... 5! 2.2 5! 2.5 

Day .................................................................................... 3 1.4 4 1.6 

Week .................................................................................. 20 3.2 21 3.5 

Month ................................................................................ 34 4.5 36 4.3 

Year ................................................................................... 23 4.0 22 3.7 

Every two weeks ............................................................... 1! 0.6 1! 0.7 

Other .................................................................................. 15 3.5 12 3.1 

 

Number of week per month in activities (ASWKMO) 

1 week ............................................................................... 27 2.9 25 3.1 

2 weeks .............................................................................. 56 3.2 57 3.4 

3 weeks .............................................................................. 16 2.5 17 2.7 

 

Amount for relative care for child only or others, 

arrangement 1 (RCCSTHH1) 

Child only .......................................................................... 48 8.6 48 9.8 

Child and others ................................................................. 52 8.6 52 9.8 

See notes at end of table. 
40 

Table 17. Relative frequency distributions for items with and without imputed values—Continued 

With imputed values Without imputed values Categorical variables Percent s.e. Percent s.e. 

 

Number of children relative care amount is for, 

arrangement 1 (RCCSTHN1) 

2 children ........................................................................... 67 11.4 68 12.9 

3 children ........................................................................... 17 6.3 15 5.9 

4 children ........................................................................... 16! 13.6 17! 15.2 

 

Amount for center-based care for child only or others, 

arrangement 1 (CPCSTHH1) 

Child only .......................................................................... 91 1.4 92 1.5 

Child and others ................................................................. 9 1.4 8 1.5 

Number of days per week in activity (ASDAYWK) 

1 day .................................................................................. 67 3.5 68 3.5 

2 days ................................................................................. 23 3.1 21 3.2 

3 days ................................................................................. 5 1.3 5 1.2 

4 days ................................................................................. 2 0.9 2 1.0 

5 days ................................................................................. 4 1.5 4 1.7 

Number of weeks per month child receives relative care, 

arrangement 1 (RCWKMO1) 

1 week ............................................................................... 50 12.0 49 14.2 

2 weeks .............................................................................. 50 12.0 51 14.2 

 

Number of weeks per month child in self-care (SCWKMO) 

1 week ............................................................................... 68 9.8 72 11.0 

2 weeks .............................................................................. 30 9.6 27 11.0 

3 weeks .............................................................................. 1! 0.9 1! 1.2 

 

Number of children center-based amount is for, 

arrangement 1 (CPCSTHN1) 

2 children ........................................................................... 80 8.0 79 9.2 

3 children ........................................................................... 17! 7.7 17! 8.9 

4 children ........................................................................... 3! 3.1 4! 3.7 

AE 

Vocational completion year, program 1 (VOCOMPY1) 

Never completed ................................................................ 5 2.3 6 2.7 

Do not intend to complete ................................................. 5 2.2 3 1.7 

2004 ................................................................................... 46 5.3 46 5.8 

2005 ................................................................................... 30 4.3 30 4.0 

2006 ................................................................................... 10 2.7 11 3.1 

2007 ................................................................................... 3! 1.7 3! 2.0 

2009 ................................................................................... 2! 1.7 1! 1.1 

See notes at end of table. 
41 

Table 17. Relative frequency distributions for items with and without imputed values—Continued 

With imputed values Without imputed values Categorical variables Percent s.e. Percent s.e. 

 

Degree/credential completion year, program 2 

(CRCOMPY2) 

Never completed ............................................................ 1! 1.1 1! 1.2 

Do not intend to complete ............................................. 2! 1.0 2! 1.1 

2004 ............................................................................... 14 3.3 13 3.5 

2005 ............................................................................... 22 4.7 20 4.9 

2006 ............................................................................... 25 6.1 25 6.8 

2007 ............................................................................... 25 5.4 28 6.0 

2008 ............................................................................... 3! 1.8 3! 2.0 

2009 ............................................................................... 5! 3.9 5! 4.3 

2010 ............................................................................... 4! 2.8 2! 2.0 

 

Apprenticeship completion year (APCOMPYY) 

Never completed ............................................................ 8 3.5 7 3.7 

Do not intend to complete ............................................. 7 2.8 7 3.1 

2004 ............................................................................... 36 7.4 36 8.3 

2005 ............................................................................... 34 7.7 35 8.2 

2006 ............................................................................... 11 5.1 11 5.9 

2008 ............................................................................... 1! 1.1 1! 1.3 

2009 ............................................................................... 3! 2.1 3! 2.5 

 

Degree/credential start year, program 2 (CRSTRTY2) 

1990 ............................................................................... 1! 0.7 1! 0.8 

1995 ............................................................................... # † 1! 0.6 

1997 ............................................................................... 1! 0.5 # † 

1998 ............................................................................... 1! 0.9 1! 1.0 

1999 ............................................................................... 2! 0.8 1! 0.8 

2000 ............................................................................... 4! 2.5 5! 2.9 

2001 ............................................................................... 12 4.6 12 5.2 

2002 ............................................................................... 5 1.7 5 2.0 

2003 ............................................................................... 26 5.7 22 4.7 

2004 ............................................................................... 32 6.4 35 7.2 

2005 ............................................................................... 17 5.6 17 6.3 

 

See notes at end of table. 
42 

Table 17. Relative frequency distributions for items with and without imputed values—Continued 

With imputed values Without imputed values Categorical variables Percent s.e. Percent s.e. 

How long enrolled in vocational program 1, number of 

months (VOENRNU1/VOENRUN1) 

1 month .......................................................................... 17 5.1 18 5.2 

2 months ........................................................................ 12 4.7 12 4.7 

3 months ........................................................................ 18 5.8 19 6.2 

4 months ........................................................................ 5! 3.4 5! 3.7 

5 months ........................................................................ 6 2.9 5 2.9 

6 months ........................................................................ 13 5.4 12 4.7 

7 months ........................................................................ 3! 1.9 3! 2.0 

8 months ........................................................................ 14! 7.5 14! 8.0 

9 months ........................................................................ 5! 2.5 5! 2.7 

10 months ...................................................................... 1! 1.1 1! 0.7 

12 months ...................................................................... 6! 2.8 6! 3.1 

 

How long enrolled in vocational program 1, number of 

semesters (VOENRNU1/VOENRUN1) 

 1 semester ...................................................................... 62 10.9 59 13.3 

2 semesters .................................................................... 19 6.6 27 10.2 

3 semesters .................................................................... 10! 5.6 9! 6.0 

4 semesters .................................................................... 9! 5.6 6! 3.8 

 

How long enrolled in vocational program 1, number of 

quarters (VOENRNU1/VOENRUN1) 

1 quarter ......................................................................... 27 10.7 27 10.9 

2 quarters ....................................................................... 23! 13.6 23! 13.8 

3 quarters ....................................................................... 27! 14.9 26! 15.0 

4 quarters ....................................................................... 24 10.2 24 10.2 

 

Employer required to take degree/credential program 2 

(CREMPRE2) 

Yes ................................................................................. 6 2.6 5 2.2 

No .................................................................................. 94 2.6 95 2.2 

 

Took degree/credential program 2 at workplace 

(CRWRKPL2) 

Yes ................................................................................. 14 5.4 13 6.0 

No .................................................................................. 86 5.4 87 6.0 

Yes ................................................................................. 23 7.2 23 7.2 

No .................................................................................. 77 7.2 77 7.2 

Being paid while taking degree/credential program 2 

(CREMPAI2) 

Yes ................................................................................. 10 3.4 10 3.5 

No .................................................................................. 90 3.4 90 3.5 

See notes at end of table. 
43 

Table 17. Relative frequency distributions for items with and without imputed values—Continued 

With imputed values Without imputed values Categorical variables Percent s.e. Percent s.e. 

 

Employer paid for books/materials for degree/credential 

program 2 (CREMPMA2) 

Yes ................................................................................. 18 6.0 19 6.6 

No .................................................................................. 82 6.0 81 6.6 

 

Degree/credential program 2 start month (CRSTRTM2) 

January .......................................................................... 28 6.3 29 6.7 

February ........................................................................ 2! 1.1 2! 1.2 

April .............................................................................. # † # † 

May ................................................................................ 1! 0.5 1! 0.6 

June ................................................................................ 12 3.6 11 3.9 

July ................................................................................ 4! 2.2 4! 2.5 

August ........................................................................... 20! 5.7 18! 4.9 

September ...................................................................... 23! 5.1 24! 5.6 

October .......................................................................... 7! 4.2 7! 4.6 

November ...................................................................... 2! 1.0 1! 0.5 

December ....................................................................... 2! 1.8 2! 1.8 

 

Degree/credential program 2 completion month 

(CRCOMPM2) 

January .......................................................................... 2! 1.1 2! 1.2 

February ........................................................................ # † # † 

April .............................................................................. 4! 2.9 4! 3.2 

May ................................................................................ 40 6.4 41 6.9 

June ................................................................................ 17 5.4 17 6.0 

July ................................................................................ 3! 1.9 2! 1.7 

August ........................................................................... 8 3.3 9 3.7 

September ...................................................................... 2! 1.2 1! 0.9 

October .......................................................................... 3! 2.3 4! 2.5 

November ...................................................................... 1! 1.2 1! 1.3 

December ....................................................................... 17 4.0 16 4.0 

Never completed ............................................................ 1! 1.1 1! 1.2 

Do not intend to complete ............................................. 2! 1.0 2! 1.1 

 

Employer paid tuition/fees, degree/credential program 2 

(CREMPTU2) 

Yes ..................................................................................... 34 6.2 33 6.8 

No ...................................................................................... 66 6.2 67 6.8 

 

See notes at end of table. 
44 

Table 17. Relative frequency distributions for items with and without imputed values—Continued 

With imputed values Without imputed values Categorical variables Percent s.e. Percent s.e. 

 

Apprenticeship program start month (APSTRTMM) 

January .......................................................................... 22 7.9 18 7.4 

February ........................................................................ 11 4.5 11 4.4 

March ............................................................................ 6! 4.8 7! 5.5 

April .............................................................................. 7! 3.9 7! 4.3 

May ................................................................................ 4! 2.1 5! 2.5 

June ................................................................................ 7 3.0 7 3.4 

July ................................................................................ 11 4.1 10 3.9 

August ........................................................................... 8 3.3 9 3.8 

September ...................................................................... 5! 2.3 5! 2.7 

October .......................................................................... 11! 6.4 11! 7.3 

November ...................................................................... 3! 1.6 3! 1.7 

December ....................................................................... 6! 4.4 7! 5.0 

 

Enrolled part-time, full-time, or both in degree/credential 

program 2 (CRPTFT2) 

Part-time ........................................................................ 51 6.0 47 6.4 

Full-time ........................................................................ 37 5.8 39 6.7 

Both part-time and full-time .......................................... 12 4.7 14 5.4 

 

Total household income range (HINCMRNG) 

$25,000 or less ............................................................... 22 0.0 22 0.3 

More than $25,000 ........................................................ 78 0.0 78 0.3 

 

Apprenticeship program completion month 

(APCOMPMM) 

January .......................................................................... 3! 1.4 3! 1.7 

February ........................................................................ 15 6.9 11 6.2 

March ............................................................................ 14 5.4 13 5.8 

April .............................................................................. 8 3.8 8 4.3 

May ................................................................................ 15 5.9 17 6.8 

June ................................................................................ 6 2.7 7 3.2 

July ................................................................................ 4! 2.3 5! 2.7 

August ........................................................................... 2! 1.3 2! 1.6 

September ...................................................................... 2! 1.7 3! 2.0 

October........................................................................... 3! 2.0 3! 2.0 

November ...................................................................... 5 2.2 5 2.7 

December ....................................................................... 8! 4.6 10! 5.3 

Never completed ............................................................ 8 3.5 7 3.8 

Do not intend to complete ............................................. 7 2.8 7 3.2 

 

Total household income range (HINCM50K)1 

$25,001 to $50,000 ........................................................ 35 0.9 35 0.9 

More than $50,000 ........................................................ 65 0.9 65 0.9 

 

See notes at end of table. 
45 

Table 17. Relative frequency distributions for items with and without imputed values—Continued 

With imputed values Without imputed values Categorical variables Percent s.e. Percent s.e. 

 

How long enrolled in degree/credential program 2, number 

of months (CRENRNU2/CRENRUN2) 

1 month .......................................................................... 39 6.9 42 7.5 

2 months ........................................................................ 39 7.1 35 8.3 

3 months ........................................................................ 15 4.2 15 4.3 

4 months ........................................................................ 7 3.0 8 3.8 

 

How long enrolled in degree/credential program 2, number 

of semesters (CRENRNU2/CRENRUN2) 

1 semester ...................................................................... 25! 24.6 30! 29.4 

2 semesters .................................................................... 27! 16.4 19! 15.0 

3 semesters .................................................................... 12! 7.2 9! 6.7 

4 semesters .................................................................... 36! 19.2 43! 23.8 

 

How long enrolled in degree/credential program 2, other 

(CRENRNU2/CRENRUN2) 

1 (unit other than semester or quarter) ........................... 79! 79.8 92! 92.0 

2 (unit other than semester or quarter) ........................... 7! 25.4 8! 92.0 

6 (unit other than semester or quarter) ........................... 14! 55.8 # † 

 

Total household income (HINCOME) 

$5,000 or less ................................................................. 3 0.2 3 0.2 

$5,001 to $10,000 .......................................................... 4 0.2 3 0.3 

$10,001 to $15,000 ........................................................ 5 0.3 5 0.4 

$15,001 to $20,000 ........................................................ 5 0.3 5 0.3 

$20,001 to $25,000 ........................................................ 6 0.3 6 0.4 

$25,001 to $30,000 ........................................................ 6 0.4 6 0.5 

$30,001 to $35,000 ........................................................ 5 0.3 5 0.4 

$35,001 to $40,000 ........................................................ 6 0.5 6 0.5 

$40,001 to $45,000 ........................................................ 4 0.3 4 0.3 

$45,001 to $50,000 ........................................................ 6 0.6 6 0.5 

$50,001 to $60,000 ........................................................ 11 0.5 11 0.6 

$60,001 to $75,000 ........................................................ 12 0.5 12 0.6 

$75,001 to $100,000 ...................................................... 13 0.5 13 0.5 

Over $100,001 ............................................................... 16 0.5 16 0.5 

! Interpret data with caution; coefficient of variation is 50 percent or more.

† Not applicable. 

# Rounds to zero. 

1

 Households with incomes of $25,000 or less did not receive this item and were excluded from this calculation. 

NOTE: s.e. is standard error. Detail may not sum to totals because of rounding. 

SOURCE: U.S. Department of Education, National Center for Education Statistics, Early Childhood Program 

Participation (ECPP) Survey of the National Household Education Surveys Program (NHES), 2005, After School 

Programs and Activities (ASPA) Survey of the National Household Education Surveys Program (NHES), 2005, and 

Adult Education (AE) Survey of the National Household Education Surveys Program (NHES), 2005. 
46 

3.3 Using Extreme Assumptions to Assess the Potential for Item 

Nonresponse Bias 

The findings reported in the previous section indicate that imputation did not alter the item 

distributions. In order to further assess possible nonresponse bias for items from each extended interview, 

new sets of imputed values were generated by imposing extreme assumptions on the item 

nonrespondents. For most items, two new sets of imputed values—one based on a “low” assumption and 

one based on a “high” assumption—were created. For most continuous variables, a “low” imputed value 

variable was created by resetting imputed values to the value at the 5th percentile of the original 

distribution; a “high” imputed value variable was created by resetting imputed values to the value at the 

95th percentile of the original distribution. For dichotomous and most polytomous variables, a “low” 

imputed value variable was created by resetting imputed values to the lowest value in the original 

distribution, and a “high” imputed value variable was created by resetting imputed values to the highest 

value in the original distribution. Both the “low” imputed value variable distributions and the “high” 

imputed value variable distributions were compared to the original distributions. 

The purpose of creating extreme assumption variables and comparing them to the original 

distributions is to place bounds on the potential for item nonresponse bias through the use of “worst case” 

scenarios. Because the distributions of many of the variables included in this evaluation are highly 

skewed, the extreme assumptions imposed here may, in some cases, be unrealistic. Also, in general, there 

is a very high correlation between estimates when comparing the extreme imputed value variables to the 

original variables, since these estimates are based on the same sets of cases and the data for respondents 

did not change.13 As a result, even small differences may be statistically significant, so it is important to 

also consider the practical or substantive significance of such differences. 

In some cases, a single extreme imputed value variable was created. For variables with 

responses heavily concentrated in a single response category, an extreme imputed value variable was 

created by assigning the nonresponding cases in approximately equal numbers to the response values.14

For variables that captured cost and unit of various child care arrangements, such as NCCOST2/ 

NCUNIT2 in ECPP and CPCOST1/CPUNIT1, CPCOST2/CPUNIT2, and NCCOST2/NCUNIT2 in 

 

13 As noted in section 1.3, these correlations were accounted for in the tests for statistical significance. 

14 This is considered extreme, because the respondent distribution for these types of items are highly skewed. This approach was used for the 

ECPP variables RCCSTHN1 and RCWKMO2, and ASPA variables ASWKMO, RCCSTHN1, CPCSTHN1, and ASDAYWK. 
47 

ASPA, extreme imputed value variables were not created, because the cost extremes depend on the unit 

and it is not possible to convert these cost variables to a single metric since the costs reported could cover 

different time units. 

Additional techniques were used for AE variables containing information about start and 

completion time for various educational programs. In order to make useful comparisons, new variables 

were created for time spent in some educational programs by computing the total number of calendar 

months each respondent was expected to be enrolled in the program. The extreme imputed value variable 

was computed by using the earliest starting year and month and the latest expected completion year and 

month, and then converting this to total calendar months in the program.15 Survey participants who 

reported “Never completed” or “Do not intend to complete” were excluded from this part of the analysis. 

Additionally, the variable EARNAMT (earnings in a 12 month period) was paired with EARNUNT (unit 

for EARNAMT: hour, day, week, bi-weekly, month, year) to derive a total earnings per year variable 

(called EARNAMTYR). Extreme imputed value variables for EARNAMTYR were created using the 5th

and the 95th percentiles of the respondent distribution, as described earlier. For variables that captured 

enrollment time and unit of various adult education activities, such as VOENRNU1/VOENRUN1 and 

CRENRNU2/CRENRUN2, extreme assumption variables were not created, since the enrollment time 

extremes depend on the unit. 

ECPP. Extreme imputed value variables were created for two variables from the ECPP 

Survey: the number of children in the household for which the relative care fee applies for the first 

relative care arrangement (RCCSTHN1), and the number of weeks per month the child receives relative 

care for the second relative care arrangement (RCWKMO2). As described earlier, an extreme imputed 

value variable was created by assigning one-third of the nonrespondents to each of the three categories. 

The original and extreme imputed value variable distributions were compared (see table 18) and no 

measurable differences were found for either variable. 

 

15 Total months in a particular program variables created for AE include CRTIME2 for the second credential program, VOTIME1 for the first 

vocational program, and APTIME for the apprenticeship program. 
48 

Table 18. Comparison of original and extreme imputed value variable estimates, for items with 

one extreme imputed value variable: 2005 

Variable 

Original 

estimate 

(percent) s.e. 

Extreme imputed 

value estimate 

(percent) s.e. 

 

ECPP 

Number of children relative care amount is for, arrangement 1 

(RCCSTHN1) 

2 children .............................................................................. 86 6.0 78 6.7 

3 children .............................................................................. 5 2.0 8 2.9 

4 children .............................................................................. 9! 6.1 14! 6.7 

 

Number of weeks per month child receives relative care, 

arrangement 2 (RCWKMO2) 

1 week .................................................................................. 64 8.5 55 10.4 

2 weeks ................................................................................. 32 7.8 30 8.1 

3 weeks ................................................................................. 5! 3.5 14! 7.2 

 

ASPA 

Number of week per month in activities (ASWKMO) 

1 week .................................................................................. 27 2.9 26 2.9 

2 weeks ................................................................................. 56 3.2 54 3.5 

3 weeks ................................................................................. 16 2.5 20 2.9 

 

Number of children relative care amount is for, arrangement 1 

(RCCSTHN1) 

2 children .............................................................................. 67 11.4 64 11.0 

3 children .............................................................................. 17 6.3 15 5.5 

4 children .............................................................................. 16! 13.6 21! 13.1 

 

Number of children center-based care amount is for, 

arrangement 1 (CPCSTHN1) 

2 children .............................................................................. 80 8.0 71 7.9 

3 children .............................................................................. 17 7.7 21 7.8 

4 children .............................................................................. 3! 3.1 8! 3.9 

 

Number of days per week in activity (ASDAYWK) 

1 day ..................................................................................... 67 3.5 64 3.5 

2 days .................................................................................... 23 3.1 22 3.2 

3 days ................................................................................... 5 1.3 8 1.8 

4 days ................................................................................... 2 0.9 2 0.9 

5 days ................................................................................... 4 1.5 3 1.5 

 

See notes at end of table. 
49 

Table 18. Comparison of original and extreme imputed value variable estimates, for items with 

one extreme imputed value variable: 2005—Continued 

Variable 

Original 

estimate 

(percent) s.e. 

Extreme imputed 

value estimate 

(percent) s.e. 

 

AE 

Derived total months in vocational program 1 (VOTIME1) .. 19 2.4 30 4.2 

Derived total months in degree/credential program 2 

(CRTIME2) ........................................................................ 39 2.8 66 7.9 

Derived total months in apprenticeship program (APTIME) . 22 3.6 31 5.5 

! Interpret data with caution; coefficient of variation is 50 percent or more.

NOTE: s.e. is standard error. Detail may not sum to totals because of rounding. 

SOURCE: U.S. Department of Education, National Center for Education Statistics, Early Childhood Program 

Participation (ECPP) Survey of the National Household Education Surveys Program (NHES), 2005, After School 

Programs and Activities (ASPA) Survey of the National Household Education Surveys Program (NHES), 2005, 

Adult Education (AE) Survey of the National Household Education Surveys Program (NHES), 2005.

ASPA. Extreme imputed value variables were formulated for ten variables from the ASPA 

Survey. For four categorical variables, including the number of weeks per month child receives relative 

care for the first relative care arrangement (RCWKMO1), if the amount paid for relative care is for child 

only or for child and others for the first relative care arrangement (RCCSTHH1), if the amount paid for 

center-based care is for child only or for child and others for the first center-based care arrangement 

(CPCSTHH1), and the number of weeks per month the child is responsible for him or herself 

(SCWKMO), both “low” and “high” extreme imputed value variables were created as described earlier. 

The original distributions were compared to the “low” and “high” imputed value variable 

distributions (see table 19). There were no measurable differences found in the comparisons of low to 

original and original to high distributions between estimates for RCWKMO1. For RCCSTHH1, there 

were measurable differences between the distributions of both the low and high imputed value variables 

and the original variable. For CPCSTHH1, there was a measurable difference between the distribution of 

the high imputed value variable and the original variable; however, the original distribution is highly 

skewed towards the first response category (91 percent for category 1 vs. 9 percent for category 2), so the 

extreme assumptions used here are likely to be unrealistic. For SCWKMO, there is a measurable 

difference between the distributions of the original and high imputed value variables, but no measurable 

difference between the distributions of the original and low imputed value variables. 
50 

Table 19. Comparison of original and extreme imputed value variable estimates, for items with 

low and high extreme imputed value variables: 2005 

Variable 

Low 

imputed 

value 

estimate 

(percent) s.e. 

Original 

estimate 

(percent) s.e. 

High 

imputed 

value 

estimate 

(percent) s.e. 

 

ASPA 

Number of weeks per month child receives relative 

care, arrangement 1 (RCWKMO1) 

1 week .................................................................... 57 12.5 50 12.0 42 12.5 

2 weeks ................................................................... 43 12.5 50 12.0 58 12.5 

 

Amount for relative care for child only or others, 

arrangement 1 (RCCSTHH1) 

Child only ............................................................... 53 8.9 48 8.6 43 8.9 

Child and others ...................................................... 47 8.9 52 8.6 57 8.9 

 

Amount for center-based care for child only or others, 

arrangement 1 (CPCSTHH1) 

Child only ............................................................... 92 1.4 91 1.4 82 2.0 

Child and others ...................................................... 8 1.4 9 1.4 18 2.0 

 

Number of weeks per month child in self-care 

(SCWKMO) 

1 week .................................................................... 77 9.0 68 9.8 59 10.3 

2 weeks ................................................................... 22 9.0 30 9.6 40 10.1 

3 weeks ................................................................... 1! 0.9 1! 0.9 1! 0.9 

 

Number of kids in center-based arrangement 1 

(CPKIDS1 ) ........................................................... 17 0.4 20 0.4 24 0.5 

Number of hours per week in activity (ASHRWK) .. 2 0.1 3 0.1 3 0.2 

AE 

Employer required to take degree/credential program 

2 (CREMPRE2) 

Yes .......................................................................... 13 3.4 6 2.6 4 2.1 

No ........................................................................... 87 3.4 94 2.6 96 2.1 

 

Took degree/credential program 2 at workplace 

(CRWRKPL2) 

Yes .......................................................................... 21 6.8 14 5.4 12 5.4 

No ........................................................................... 79 6.8 86 5.4 88 5.4 

 

See notes at end of table. 
51 

Table 19. Comparison of original and extreme imputed value variable estimates, for items with 

low and high extreme imputed value variables: 2005—Continued 

Variable 

Low 

imputed 

value 

estimate 

(percent) s.e. 

Original 

estimate 

(percent) s.e. 

High 

imputed 

value 

estimate 

(percent) s.e. 

 

Took degree/credential program 2 during work hours 

(CRWRKHR2) 

Yes .......................................................................... 30 7.5 23 7.2 12 5.4 

No ........................................................................... 70 7.5 77 7.2 88 5.4 

 

Being paid while taking degree/credential program 2 

(CREMPAI2) 

Yes .......................................................................... 18 4.2 10 3.4 9 3.2 

No ........................................................................... 82 4.2 90 3.4 91 3.2 

 

Employer paid for books/materials for degree/ 

credential program 2 (CREMPMA2) 

Yes .......................................................................... 26 6.9 18 6.0 17 6.0 

No ........................................................................... 74 6.9 82 6.0 83 6.0 

 

Employer paid tuition/fees, degree/credential program 

2 (CREMPTU2) 

Yes .......................................................................... 40 7.1 34 6.2 30 5.9 

No ........................................................................... 60 7.1 66 6.2 70 5.9 

 

Enrolled part-time, full-time, or both in degree/ 

credential program 2 (CRPTFT2) 

Full-time ................................................................. 54 5.8 51 6.0 41 6.1 

Part-time ................................................................. 33 5.9 37 5.8 47 6.6 

Both part-time and full-time ................................... 12 4.7 12 4.7 12 4.7 

 

Total hours attended ABE/GED (BSHRYR) ............ 51 9.1 61 11.3 73 12.9 

 

Personal expenses for tuition/fees, degree/credential 

program 2 (CRTUITO2) ....................................... 3,428 889.9 3,801 866.8 6,154 981.2 

 

Total degree/credential credit hours enrolled, program 

2 (CRCRDHR2) .................................................... 15 1.6 16 1.5 17 1.6 

Total vocational classroom hours, program 1 

(VOCLSHR1) ....................................................... 67 12.9 95 14.5 153 17.0 

 

Total vocational credit hours enrolled, program 1 

(VOCRDHR1) ...................................................... 16 3.4 21 3.5 32 4.1 

 

See notes at end of table. 
52 

Table 19. Comparison of original and extreme imputed value variable estimates, for items with 

low and high extreme imputed value variables: 2005—Continued 

Variable 

Low 

imputed 

value 

estimate 

(percent) s.e. 

Original 

estimate 

(percent) s.e. 

High 

imputed 

value 

estimate 

(percent) s.e. 

 

Total apprenticeship classroom instruction hours 

(APCLSHR) .......................................................... 42 6.5 62 8.3 93 11.8 

Personal expenses for books/materials, degree/ 

credential program 2 (CRMATLS2) ..................... 341 58.6 372 62.5 454 61.0 

Total household income range (HINCMRNG) 

$25,000 or less ........................................................ 33 0.4 22 0.0 19 0.3 

More than $25,000 ................................................. 67 0.4 78 0.0 81 0.3 

 

Total household income range (HINCM50K)2 

$25,001 to $50,000 ................................................. 46 0.8 35 0.9 29 0.8 

More than $50,000 ................................................. 54 0.8 65 0.9 71 0.8 

 

Total household income (HINCOME) 

$5,000 or less ......................................................... 24 0.7 3 0.2 2 0.2 

$5,001 to $10,000 ................................................... 2 0.2 4 0.2 2 0.2 

$10,001 to $15,000 ................................................. 4 0.3 5 0.3 4 0.3 

$15,001 to $20,000 ................................................. 4 0.3 5 0.3 4 0.3 

$20,001 to $25,000 ................................................. 5 0.3 6 0.3 5 0.3 

$25,001 to $30,000 ................................................. 5 0.4 6 0.4 5 0.4 

$30,001 to $35,000 ................................................. 4 0.3 5 0.3 4 0.3 

$35,001 to $40,000 ................................................. 4 0.4 6 0.5 4 0.4 

$40,001 to $45,000 ................................................. 3 0.3 4 0.3 3 0.3 

$45,001 to $50,000 ................................................. 5 0.4 6 0.6 5 0.4 

$50,001 to $60,000 ................................................. 9 0.5 11 0.5 9 0.5 

$60,001 to $75,000 ................................................. 9 0.5 12 0.5 9 0.5 

$75,001 to $100,000 ............................................... 10 0.4 13 0.5 10 0.4 

Over $100,001 ........................................................ 13 0.4 16 0.5 35 0.8 

 

Derived earnings per year (EARNAMTYR)1 ........... 23,924 569.4 39,243 597.9 51,808 859.2 

 

! Interpret data with caution; coefficient of variation is 50 percent or more.

1 EARNAMTYR is derived from EARNAMT and EARNUNT to create an annual earnings variable for analysis. 2

 Households with incomes of $25,000 or less did not receive this item and were not included in this calculation. 

NOTE: s.e. is standard error. Detail may not sum to totals because of rounding. 

SOURCE: U.S. Department of Education, National Center for Education Statistics, After School Programs and 

Activities (ASPA) Survey of the National Household Education Surveys Program (NHES), 2005, Adult Education 

(AE) Survey of the National Household Education Surveys Program (NHES), 2005. 
53 

For four variables, including the number of weeks per month the child participates in 

activities or lessons after school (ASWKMO), the number of children in the household for which the 

relative care fee applies for the first relative care arrangement (RCCSTHN1), the number of children in 

the household for which the center-based care fee applies for the first center-based care arrangement 

(CPCSTHN1), and the number of days per week the child does activities or lessons after school 

(ASDAYWK), one extreme imputed value variable was created as for polytomous variables described 

earlier. The original and extreme imputed value variable distributions were compared (see table 18) and 

no measurable differences in distributions were found for ASWKMO, RCCSTHN1, or ASDAYWK. For 

CPCSTHN1, the distributions of the two variables differ, but since the original distribution is skewed 

towards the first response category, the extreme assumptions used may be unrealistic. 

For the two continuous variables including the number of children in the program in the first 

center-based care arrangement (CPKIDS1) and the number of hours per week the child does activities or 

programs after school (ASHRWK), the low and high extreme imputed value variables were created as 

described earlier. The means of the extreme imputed value variables were compared to the original means 

(see table 19). For ASHRWK, differences were found between both the low imputed value variable and 

original means, and the original and high imputed value variable means. Similar to the variable 

CPCSTHH1, the original distribution of ASHRWK is highly skewed towards the first two response 

categories (about 90 percent of respondents reported values of 1 or 2 hours) which indicates that the 

extreme assumptions used may be unrealistic, causing a significant effect on the distribution. As noted 

earlier, these extremes were chosen to examine worst-case scenarios and to give bounds on the potential 

for item nonresponse bias. 

Measurable differences were detected in the means of CPKIDS1 between the low and 

original variable, and the original and high variable. The range of values between the low imputed value 

variable mean and the high imputed value variable mean for this item is from 17 to 24 children in the 

center-based care arrangement. 

AE. Extreme imputed value variables were formulated for 21 variables from the AE Survey. 

For seven categorical variables, including whether the employer required the degree/certificate program 

for the second program (CREMPRE2), whether the respondent is taking the degree/certificate program at 

the workplace for the second program (CRWRKPL2), whether the respondent is taking the 

degree/certificate program during regular work hours for the second program (CRWRKHR2), whether the 

respondent is being paid by employer while taking the degree/certificate program for the second program 
54 

(CREMPAI2), whether the employer paid for all or part of the costs of books and other materials for the 

second program (CREMPMA2), whether the employer paid for all or part of the tuition and fees for the 

degree/certificate program for the second program (CREMPTU2), and whether the respondent attends as 

a full-time, part-time, or both full- and part-time student for the second program (CRPTFT2), both low 

and high imputed value variables were created as described earlier. 

The original distributions were compared to the low and high imputed value variable 

distributions (see table 19). Measurable differences were detected between the original and low imputed 

value variables for all seven variables, but between the original and high imputed value variables for 

CRPTFT2 only. For all six dichotomous variables, there is a smaller concentration of respondents in the 

first response category (“yes”). 

For seven continuous variables including total hours the respondent attended the basic skills 

or high school completion classes in the last 12 months (BSHRYR), amount of the respondent’s or 

family’s money paid for tuition and fees including borrowed money in the last 12 months for the second 

degree/certificate program (CRTUITO2), total number of credit hours in which respondent was enrolled 

in the last 12 months for the second degree/certificate program (CRCRDHR2), total number of class 

hours respondent took in the last 12 months for the first vocational program (VOCLSHR1), total number 

of credit hours in which the respondent was enrolled in the last 12 months for the first vocational program 

(VOCRDHR1), total number of class hours the respondent spent in the apprenticeship program in the last 

12 months (APCLSHR), and amount of the respondent’s or family’s money paid for books or other 

materials including borrowed money in the last 12 months for the second degree/certificate program 

(CRMATLS2), both low and high extreme imputed value variables were created as described earlier. The 

means of these extreme imputed value variables were compared to the original means (see table 19). No 

measurable differences were found when comparing the means for BSHRYR. Differences were found for 

CRCRDHR2, VOCLSHR1, VOCRDHR1, and APCLSHR between the original means and both the low 

and high extreme imputed value variable means. For this set of variables, it is important to note the 

skewness of the distributions and the range of values. Since these variables are reports of classroom hours 

or credit hours for adult education participation programs, the ranges are rather large and the distributions 

are skewed. For CRTUITO2, a difference was found between the original and low imputed value variable 

means, but not between the original and high imputed value variable means. For CRMATLS2, a 

difference was found between the original and high imputed value variable means, but not the original 

and low imputed value variable means. 
55 

The three derived variables VOTIME1, CRTIME2, and APTIME that capture total number 

of months in the first vocational program, second credential program, or apprenticeship program, 

respectively, were each compared to one extreme imputed value variable as described earlier. The original 

and extreme imputed value variable means were compared (see table 18), and there were differences for 

all three variables. As with CRCRDHR2, VOCRDHR1, VOCLSHR1 and APCLSHR mentioned earlier, 

the skewness of the distributions resulted in these differences when extreme conditions were considered, 

but the range of number of months reported in these programs indicates that these differences may not be 

substantively important. 

For the four AE items pertaining to income and earnings, HINCOME, HINCMRNG, 

HINCM50K, and the derived variable described earlier, EARNAMTYR, item response rates were 

relatively low, even in comparison with other items in this analysis. (See table 15 for item response rates.) 

In these instances, imposing extreme assumptions on the nonrespondents will affect the distributions of 

these variables. (See table 19.) Additionally, all four of these variables, in particular HINCOME and 

EARNAMTYR, had skewed distributions so that assigning all nonrespondents to a low or high extreme 

imputed value has an even more pronounced effect on the distributions. 
56 

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57 

4. Conclusions 

With survey response rates—in particular, RDD survey response rates—on the decline, the 

potential for nonresponse bias is an important concern to survey methodologists and data analysts. This 

report has included assessments of the potential for both unit and item nonresponse bias. The analysis of 

unit nonresponse bias showed no evidence of potential bias in the estimates considered from the ECPP 

and ASPA Surveys. For the AE Survey, the only evidence of unit nonresponse bias is in estimates of sex; 

females were more likely to respond than males. The weighting class adjustment for nonresponse to the 

AE Survey used sex in forming the weighting classes (see Hagedorn et al. forthcoming for details) and 

should, therefore, reduce this bias. 

The statistical adjustments used in weighting may have corrected at least partially for other 

biases that might have existed due to differential nonresponse. However, it is possible that nonresponse 

bias may still be present in other variables that were not studied. For this reason, it is important to 

consider other methods of examining unit nonresponse bias. One such method is benchmarking, or 

comparing final NHES survey estimates to estimates from external sources. Benchmarking is routinely 

done during the preparation of the NHES data files. When estimates from the NHES:2005 surveys were 

compared to external estimates (primarily from the Current Population Survey and from previous NHES 

surveys), some measurable differences were found. (See Appendix C of Hagedorn et al. forthcoming.) 

However, in nearly every case, these differences were attributable to factors other than nonresponse bias, 

such as differences in measurement. 

The analysis of item nonresponse bias included two components. The comparison of means 

or distributions, including imputed values versus excluding imputed values, revealed no measurable 

differences. From this, one can conclude that either imputation was not effective in reducing item 

nonresponse bias or that there was no item nonresponse bias present in these items. The second 

component of the item nonresponse bias analysis, the comparison of means or distributions based on 

extreme assumptions to the original means or distributions, did reveal some differences. For example, if 

the item nonrespondents differ considerably from the respondents, the potential for bias exists in the 

ASPA variable CPKIDS1, but there may be little substantive importance in the difference between the 

low and high extreme imputed value means (17 versus 24 children). Other differences that were observed 

in extremes, such as for the ASPA variables CPCSTHH1 and ASHRWK, and the AE income and 
58 

earnings variables and months in program variables, are the result of imposing extreme assumptions on 

variables with highly skewed distributions and a large range of values in the original distributions. 

It is important to consider the two components of the item nonresponse bias analysis in 

tandem. The first component (the comparison of means or distributions, including imputed values versus 

excluding imputed values) revealed no important measurable differences, thus suggesting that there was 

no reduction in item nonresponse bias. As noted above, the extreme assumptions component did reveal 

the potential for item nonresponse bias, if the item nonrespondents differ considerably from the 

respondents. However, it is that particular situation in which the hot-deck would be expected to be most 

effective in reducing item nonresponse bias; by using variables to form hot-deck cells that are associated 

with either the item itself or its item response propensity, the hot-deck reduces item nonresponse bias. 

Therefore, taken together, these two components of the item nonresponse bias analysis suggest that the 

likely scenario is that there was no substantive item nonresponse bias, and that the extreme assumptions 

imposed in this analysis are unrealistic. 
59 

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