Patterns of Item Nonresponse for Income in the 

National Survey on Drug Use and Health 

Peter Frechtel,1 Glynis Ewing,1 Kristen Brown,1 Jonaki Bose,2 Rebecca Ahrnsbrak2 

1 RTI International (a registered trademark and a trade name of Research Triangle Institute), 

Research Triangle Park, NC, USA 

2 Substance Abuse and Mental Health Services Administration, Rockville, MD, USA 

1. Introduction 

Conducted annually, the National Survey on Drug Use and Health (NSDUH) is the primary source of information 

on alcohol use, tobacco use, illicit drug use, substance use disorders, and mental health issues for the U.S. civilian, 

noninstitutionalized population aged 12 years or older. In the 2014 NSDUH, this population included residents of 

noninstitutional group quarters (e.g., shelters, rooming houses, dormitories, and group homes) and civilians residing 

on military bases. The target population excluded people with no fixed household address (e.g., homeless or 

transient people not in shelters), residents of institutional group quarters (e.g., jails and hospitals), children younger 

than 12, and active military personnel. As it has since 1999, the 2014 NSDUH utilized a 50-state, multistage cluster 

design that enables the Substance Abuse and Mental Health Services Administration (SAMHSA) to provide 

representative estimates for each state and the District of Columbia. Both direct and model-based state and substate 

estimates are produced on a variety of measures based on a combination of multiple years of data. 

Low response rates to income questions and resulting nonresponse bias are well documented in the survey research 

literature (Bollinger, Hirsch, Hokayem, & Ziliak, 2014; Tourangeau & Yan, 2007; Pleis & Dahlhamer, 2004; 

Moore, Stinson, & Welniak, Jr., 2000; Juster & Smith, 1997). Like many other household surveys, the family 

income variables measured in NSDUH have much lower response rates than the vast majority of other questionnaire 

items. Typically, approximately 90 percent of variables that underwent statistical imputation required less than 5 

percent of their records to be logically assigned or statistically imputed (Center for Behavioral Health Statistics and 

Quality, 2015, Appendix A). In 2014, 6,589 cases were missing for finer categories of total family income resulting 

in a weighted nonresponse rate of 10.46 percent. This relatively high item nonresponse rate is of interest because the 

NSDUH family income variables and their recodes are used in many analyses, and the distribution of public health 

variables by income levels has implications for policy decisions. Any steps that could be taken to reduce the impact 

of item nonresponse, to improve the imputation method, or to improve the questionnaire would be helpful with 

reducing nonresponse bias and improving overall data quality. By improving the understanding of the mechanisms 

of item nonresponse for income, this appendix describes solutions and recommendations for further addressing and 

reducing item nonresponse and/or nonresponse bias in variables measuring total family income and poverty through 

better imputation methods or by making changes to the questionnaire to reduce item nonresponse. 

2. Measurement of Total Income in NSDUH 

NSDUH estimates respondents’ total income for adults and youths aged 12 to 17 by asking about total personal 

income and total family income, based on two questions: 

1. Of these income groups, which category best represents (your/SAMPLE MEMBER’s) total personal income 

during [the previous calendar year]? 

2. Of these income groups, which category best represents (your/SAMPLE MEMBER’s) total combined family 

income during [the previous calendar year]? 

Respondents receive these questions after being routed through an unfolding bracket of related income questions in 

order to minimize income item nonresponse as much as possible. 

Family is defined as any related member in the household roster, including all foster relationships and unmarried 

partners (including same-sex partners). Roommates, boarders, and other nonrelatives are excluded from the 

definition of family for total family income. Responses from proxies are accepted for items of health insurance and 

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income from a family member living in the same household who is identified as being better able to give the correct 

information. The NSDUH questionnaire allows respondents to decline to answer any question (except age) by 

entering “Don’t know” (DK) or “Refused” (REF) as a response. 

Total family income is an important measure because it is used to establish a respondent’s poverty level using the 

NSDUH data. Poverty level is determined by comparing a respondent’s total family income with the U.S. Census 

Bureau’s poverty thresholds (both measured in dollar amounts), with a respondent’s family size and composition 

(i.e., number of children) taken into consideration. The resulting variables indicating levels of poverty are often used 

in NSDUH analyses. When total family income is missing, the poverty level is unknown. 

2.1 Questionnaire Skip Logic 

Total income is measured in NSDUH through an unfolding bracket of questionnaire items that can be understood as 

steps. These steps are illustrated in the flowchart in Figure 1. There are 29 finer categories of personal and family

income that are captured by the variables PINC2 and FINC2, respectively. Table 1 shows the binary and finer 

categories of income. 

Figure 1. 2014 NSDUH Questionnaire Measurement of Total Income 

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Table 1. Binary Categories of Personal and Family Total Income: 2014 NSDUH 

Binary Category 

(PINC1, FINC1) 

Finer Category 

(PINC2, FINC2) 

Level Description Level Description 

2 < $20,000 

1 < $1,000 

2 $1,000-$1,999 

⁞ 

20 $19,000-$19,999 

1 ≥ $20,000 

21 $20,000-$24,999 

⁞ 

26 $45,000-$49,999 

27 $50,000-$75,999 

28 $75,000-$99,999 

29 ≥ $100,0001 

1 This final measurement category of income was measured in the 2014 and previous iterations of NSDUH. 

Beginning in 2015, this category became $100,000-$149,999 and a 30th measurement category of ≥ $150,000 

was added. 

The first step of the income questionnaire module establishes whether the personal income of the respondent is 

greater than or equal to $20,000 with a binary questionnaire item. This response is captured by PINC1. The next step 

in measuring total personal income is to determine the finer category of personal income for each respondent. 

Respondents reporting personal incomes that are less than $20,000 are directed to the finer personal income 

categories with levels ranging from less than $1,000 (PINC2 = 1) to $19,000-$19,999 (PINC2 = 20). Respondents 

reporting personal incomes that are greater than or equal to $20,000 are directed to the finer personal income 

categories, ranging from $20,000-$24,999 (PINC2 = 21) to $100,000 or more (PINC2 = 29). This response is 

captured by PINC2. 

After measuring finer categories of total personal income, respondents are routed to questionnaire items measuring 

total family income depending on the presence of family members in the household. This information is reported in 

the household roster. If the respondent did not report any family members in his or her household, then the 

questionnaire item on total family income is not asked and the personal income response (PINC2) is used for total 

family income for that respondent. If the respondent reported family members in the household and the personal 

income level that is reported in PINC1 is greater than or equal to $20,000, then the respondent is directly routed to 

the finer categories of family income question, FINC2, skipping the binary family income questionnaire item 

FINC1. 

If the respondent reports the highest level of response available for personal income, $100,000 or more (PINC2 = 

29), total family income is automatically completed as $100,000 or more (FINC2 = 29). If reported personal income 

is less than $20,000, the questionnaire then asks respondents whether the total family income is greater than or equal 

to $20,000 (FINC1). Based on this response, respondents are directed to one of the two questionnaire items 

measuring finer categories of family income (captured by FINC2). FAMINC2 is the final resulting variable 

measuring the finer categories of family income. It is equal to PINC2 for those with no other family members in the 

household roster, and it is equal to FINC2 for those with other family members in the household roster. 

2.2 Paths to Income Item Nonresponse 

Because of the skip logic and questionnaire routing, there are six ways, or “paths,” in which the respondent could 

have a valid value for total family income, and there are nine opportunities for respondents to become defined as 

missing in the total family income measure (see Table 2 and Figure 2 for paths of nonresponse). The flowchart in 

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Figure 2 illustrates how and where these valid or missing values occur based on the structure of the income 

questionnaire items. The numbered missing nodes correspond with the paths of nonresponse shown in Table 2. 

Table 2. Paths of Finer Categories of Family Income Item Nonresponse: 2014 NSDUH 

Path of Income Item Nonresponse Frequency Percent 

Rank by 

Frequency 

Missing 

1 Breakoff 27 0.41 9 

2 No Family in HH, PINC1 Missing 182 2.76 6 

3 No Family in HH, PINC2 Missing 241 3.66 5 

4 Imputed to Family in HH, PINC2 ≠ 29 56 0.85 7 (tie) 

5 Family in HH, PINC1 Missing, FINC1 Missing 686 10.41 4 

6 Family in HH, PINC1 Missing, FINC1 Valid, FINC2 Missing 56 0.85 7 (tie) 

7 Family in HH, PINC1 = 1, PINC2 ≠ 29, FINC2 Missing 1,150 17.45 3 

8 Family in HH, PINC1 = 2, FINC1 Missing 1,929 29.28 2 

9 Family in HH, PINC1 = 2, FINC1 Valid, FINC2 Missing 2,262 34.33 1 

Total Income Item Nonresponse 6,589 100.00 N/A 

HH = household. 

Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 

2014. 

The two most common paths of income item nonresponse occur for sample members with personal incomes that are 

less than $20,000 living in households with family members who either (1) responded to the binary total family 

income questionnaire item but did not respond to the finer categories of total family income question 

(nonrespondents = 2,262) or (2) did not respond to the binary total family income questionnaire item and thus did 

not receive the finer categories of total family income question (nonrespondents = 1,929). The third most common 

path to item nonresponse for total family income occurs for sample members with personal incomes that are greater 

than $20,000 but less than $100,000 living in households with family members who do not answer the finer 

categories of family income question (nonrespondents = 1,150). This is followed by the fourth most common path of 

family income item nonresponse for respondents living with family members in the household who did not answer 

the binary personal or family income items at all (nonrespondents = 686). The next most common paths of family 

income item nonresponse occur for respondents without any family members living in the same household and 

either do not respond to the binary personal income questionnaire item (nonrespondents = 182) or respond to the 

binary personal income item and do not respond to the finer categories of personal income (nonrespondents = 241). 

The three remaining paths of family income item nonresponse are less common with fewer than 60 nonrespondents 

each. 

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Figure 2. Income Item Response and Nonresponse Paths with Frequencies: 2014 NSDUH 

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Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 2014. 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

3. Potential Solutions and Recommendations 

In NSDUH, income item nonresponse has historically been handled using imputation. Income is a unique measure 

because the observed nonresponse depends, in part, on the unknown values of the variable that are not actually 

observed, so income item nonresponse can be described as not missing at random (NMAR) (Bollinger et al., 2014; 

Pleis & Dahlhamer, 2004). Because income item nonresponse is NMAR, imputation involving only auxiliary 

variables does not completely correct for the present nonresponse bias and resulting measurement error (Little & 

Rubin 1987; Frechtel & Copello, 2007). However, NSDUH has certain survey features that can be used to more 

accurately decrease income item nonresponse. This section presents potential solutions and recommendations for the 

future based on reclaiming1 missing income responses from family pair members and explores how further use of 

proxy responses can improve overall data quality. 

3.1 Reclaiming with Other Family Pair Member 

In each household selected for NSDUH, zero, one, or two household members are selected for interviewing. When 

two members of the same household are selected and both complete an interview, a "pair" is formed. Pairs are quite 

common. For example, in the 2014 NSDUH, 53.7 percent of the unit respondents were members of a pair. The pair 

relationship can be parent-child, sibling-sibling, spouse-spouse, or some other relationship. 

The report on the evaluation of imputation methods for NSDUH (Center for Behavioral Health Statistics and 

Quality, in press) discusses the use of the other pair member as a donor in imputation when exactly one pair member 

is missing. In that report, family income is considered a good candidate for this sort of logical imputation whenever 

the pair members are members of the same family. Because most of the questions in the income module ask about 

the family income of those in the household, given the case where the pair members are members of the same 

family, the only source of disagreement should be measurement error (Frechtel, Scott, Couzens, Moore, & Bose, 

2012). This section describes reclaiming values of family income that sometimes involves the data reported by the 

respondent and sometimes involves the data reported by the other family pair member (OFPM) about the family. 

The following two key recoded variables involving family income are considered: 

1. INCOME5, a straightforward five-level recode of finer income; and 

2. POVERTY2, a three-level recode of not only family income but also of roster information and type of 

household. 

Although recodes on NSDUH typically do not have imputation indicators associated with them, it would be 

beneficial to add them because the imputation indicators associated with INCOME5 and POVERTY2 would differ 

from the imputation indicator for the family finer categories income variable IRFAMIN2, called IIFAMIN2. 

3.1.1 Reclaiming Missing Values for INCOME5 

Table 3 shows how the 29 levels of IRFAMIN2 map to the 5 levels of INCOME5. The highest three levels are the 

same for both variables, but the lower levels are heavily aggregated. 

Table 3. Mapping of IRFAMIN2 Levels to INCOME5 Levels 

IRFAMIN2 INCOME5 

Level Description Level Description 

1 < $1,000 

1 < $20,000 2 [$1,000, $2,000) 

⁞ ⁞

20 [$19,000, $20,000) 

21 [$20,000, $25,000) 2 [$20,000, $50,000) ⁞ ⁞

1 To "reclaim" in this context is to assign a value for a recode using logic when some or all of the parent variables 

for the recode have missing values. It might also be called "logical imputation." 

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IRFAMIN2 INCOME5 

Level Description Level Description 

26 [$45,000, $50,000) 

27 [$50,000, $75,000) 3 [$50,000, $75,000) 

28 [$75,000, $100,000) 4 [$75,000, $100,000) 

29 ≥ $100,000 5 ≥ $100,000 

There are exactly 661 respondents in the 2014 data whose missing values for IRFAMIN2 can be reclaimed using 

only the self's data. For these types of respondents, it is known that INCOME5 = 1 even though IRFAMIN2 is 

missing. This can occur in two ways: 

1. The respondent has no other family members in the household, reported having a personal income of less than 

$20,000 (PINC1 = 2), and had a missing value for the personal finer categories income variable (PINC2). 

2. The respondent has other family members in the household, reported having a family income of less than 

$20,000 (FINC1 = 2), and had a missing value for the personal finer categories income variable (FINC2). 

Using the self, 661 (10.03 percent) of the 6,589 missing values for IRFAMIN2 can be reclaimed. Of the remaining 

5,928 cases with missing values, 1,267 (21.37 percent) cases had an OFPM with a nonmissing value for FAMINC2, 

and 60 (1.01 percent) other cases had an OFPM with family binary income of less than $20,000. In total, the 

reclaiming process can reduce the item nonresponse rate for INCOME5 from 9.70 percent to 6.78 percent (Table 4). 

Table 4. Reclaiming of Missing Values of INCOME5 

Count 

Nonresponse for 

INCOME5 (%) 

Cases with Missing FAMINC2 6,589 9.70 

Minus Cases with FAMINC1 = 2 661 8.73 

Minus Cases Where OFPM Has Nonmissing FAMINC2 1,267 6.86 

Minus Cases Where OFPM Has FAMINC1 = 2 60 6.78 

Final Nonresponse Rate for INCOME5 4,601 6.78 

3.1.2 Reclaiming Missing Values for POVERTY2 

The variable POVERTY2 is a complex recode involving the imputation-revised family finer categories income 

variable IRFAMIN2, plus the respondent's age (AGE) and the roster variables IRFMLYSZ (imputation-revised 

household size including fosters) and IRKDFMLY (imputation-revised number of children in household including 

fosters). The variable is created in two steps. In the first step, the poverty threshold is calculated based on a formula 

from the U.S. Census Bureau involving values that are captured by the variables AGE, IRFMLYSZ (imputationrevised family size), and IRKDFMLY (imputation-revised number of children younger than 18 in the household).2 

In the second step, the family income variable IRFAMIN2 (actually the midpoint of the interval associated with the 

value of IRFAMIN2) is compared with the poverty threshold. POVERTY2 has four levels: 

1. The respondent is 18 to 22 years old and lives in a college dorm (POVERTY2 = missing). 

2. The family income is less than the poverty threshold (POVERTY2 = 1). 

3. The family income is greater than or equal to the poverty threshold but less than twice the poverty threshold 

(POVERTY2 = 2). 

4. The family income is greater than twice the poverty threshold (POVERTY2 = 3). 

Note that the pre-imputation versions of IRFMLYSZ and IRKDFMLY have missing values as well, but the item 

nonresponse rates for these (less than 1 percent) are much smaller in comparison with the item nonresponse rate 

associated with the pre-imputation version of IRFAMIN2 (9.70 percent weighted, 10.46 percent unweighted). 

2 See https://www.census.gov/hhes/www/poverty/data/threshld/. 

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Because of the relatively low item nonresponse rates associated with these household size variables, it is assumed 

that there are no missing data for the two household composition variables, and reclaiming efforts for POVERTY2 

are focused on obtaining valid responses from income variables for this investigation. 

In total, 1,964 cases with missing values for FAMINC2 can be reclaimed if an imputation indicator were created for 

POVERTY2. The first step in reclaiming is to calculate bounds for the family income based on both the person's 

responses and on the OFPM's responses. The possible lower bounds for FAMINC2 are the following: 

• (L1) 21, if PINC1 = 1; 

• (L2) PINC2, if 2 ≤ PINC2 ≤ 28; and 

• (L3) 21, if FINC1 = 1. 

The possible upper bounds for FAMINC2 are the following: 

• (U1) 20, if PINC1 = 2, PINC2 is missing, and the person lives with no other family members; and 

• (U2) 20, if FINC1 = 2. 

All of these bounds were calculated for both the self and the OFPM, except U1, which was only calculated for the 

self. If the self has no other family members in the household, then it is assumed that the OFPM's data would not be 

available. 

Table 5 shows the reclaiming of missing values for POVERTY2 relative to FAMINC2. Probably the most 

interesting category is the 612 cases that can be reclaimed using the self data. Of the 612 cases, 277 (45.26 percent) 

can be reclaimed because the family income is definitely greater than twice the poverty threshold, 320 (52.29 

percent) can be reclaimed because the family income is definitely less than the poverty threshold, and 15 (2.45 

percent) can be reclaimed because the family income is definitely greater than the poverty threshold and less than 

twice the poverty threshold. Overall, the reclaiming process can reduce the item nonresponse rate for POVERTY2 

from 9.70 percent to 6.81 percent. 

Table 5. Reclaiming of Missing Values of POVERTY2 

Count 

Nonresponse for 

INCOME5 (%) 

Cases with Missing FAMINC2 6,589 9.70 

Minus College Students in Dorms 8 9.69 

Minus Cases Where POVERTY2 Value Can Be Determined 

Based on the Self Data 612 8.79 

Minus Cases Where OFPM Has Nonmissing FAMINC2 1,288 6.89 

Minus Cases Where POVERTY2 Value Can Be Determined 

Using Bounds from the OFPM Data 56 6.81 

Final Nonresponse Rate for POVERTY2 4,625 6.81 

3.1.3 Next Steps for Reclaiming Income with Other Family Pair Member 

One problem with editing income using the OFPM data is that a direct assignment can create an inconsistent record. 

There are 130 cases in the 2014 data where a direct assignment of the OFPM's value for FAMINC2 would create an 

inconsistent record. These are mostly cases where the self has FINC1 = 1 and the OFPM has FINC1 = 2, or the self 

has FINC1 = 2 and the OFPM has FINC1 = 1. There are also 24 cases in the 2014 data where the OFPM has a 

missing value for FAMINC2, but the bounds based on the OFPM's responses are inconsistent with bounds based on 

the self's responses. For example, the self might have FINC1 = 2, the OFPM might have FINC1 = 1, and both pair 

members might have FINC2 missing. 

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The direct-assignment approach rests on an implicit assumption that these pair members agree when they both 

respond. This is not always the case. When both family pair members responded in the 2014 survey, they agreed 

68.64 percent of the time, suggesting that there is non-negligible measurement error present (Table 6). Sometimes 

the responses of the family pair members are quite different. For example, they disagreed by greater than four or 

more levels of FAMINC2 8.59 percent of the time. 

Table 6. Disagreement in Family Income among Family Pair Members: 2014 NSDUH 

Number of Income Levels 

between Paired Responses Number of Family Pairs Percentage of Family Pairs 

0 9,441 68.64 

1 2,013 14.63 

2 754 5.48 

3 366 2.66 

4+ 1,181 8.59 

Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 

2014. 

The response agreement between the responding family pair members across pair types shows that the agreement 

rates for grandparent-grandchild pairs (56.99 percent) and spouse-spouse pairs (57.36 percent) are lowest, and the 

agreement rates among sibling-sibling pairs where one of the pair members is aged 12 to 14 are highest (84.51 

percent) (Table 7). The low agreement rate for spouse-spouse pairs may suggest measurement error associated with 

a lack of knowledge. The relatively high agreement rates among parent-child pairs where one of the pair members is 

aged 12 to 14 (77.66 percent) or 15 to 17 (77.65 percent) may be a result of the higher number of proxy responses 

for the family income item in this age group, and it is possible that the parent pair member gave responses as a proxy 

for the child pair member. 

Table 7. Agreement by Pair Type among Responding Pairs for Family Finer Categories Income: 2014 

NSDUH 

Pair Type 

Responding Pairs 

Number Percent Percent Agreement among Pairs 

Parent-Child, Child Aged 12-14 2,596 41.63 77.66 

Parent- Child, Child Aged 15-17 2,139 34.40 77.65 

Parent- Child, Child Aged 18-20 711 11.40 59.92 

Parent- Child, Child Aged 21+ 790 12.67 56.33 

Parent-Child Total 6,236 100.00 72.93 

Sibling-Sibling, Youngest 12-14/Oldest 15-17 1,291 31.00 84.51 

Sibling-Sibling, Youngest 12-17/Oldest 18-25 1,330 31.94 63.53 

Sibling-Sibling, Other Age Pairings 1,543 37.06 66.88 

Sibling-Sibling Total 4,164 100.00 71.28 

Spouse-Spouse with Children 1,631 51.55 56.59 

Spouse-Spouse without Children 1,511 47.76 58.37 

Spouse-Spouse, Children Not Clear 22 0.70 45.45 

Spouse-Spouse Total 3,164 100.00 57.36 

Grandparent-Grandchild 193 100.00 56.99 

Overall Total 13,757 100.00 68.63 

Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 

2014. 

A caveat to using OFPM data is that sometimes the pair members disagree on whether they are part of a family. 

Other-pair-member roster editing has revealed that, especially for blended families and families involving unmarried 

partners, the pair members occasionally disagree on the nature of their relationship. The imputation-revised familyskip variable IRFAMSKP does not have to be consistent among the pair members (though the imputation-revised 

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pair relationship variable IRPRREL does), and those with IRFAMSKP = 1 are automatically assigned skip codes for 

edited and imputation-revised income variables related to the family. 

For these reasons, if these methods were to be put into practice, it is recommended that the OFPM's values be used 

only if all three of the following conditions are met: 

1. According to IRPRREL, the pair members are members of the same family. 

2. Both pair members have IRFAMSKP = 0. 

3. The values of the other pair member are consistent with the nonmissing responses given by the respondent. 

3.2 Proxy Respondents 

Respondents’ selection of a proxy tends to improve the response rate for income variables. The next step is to 

examine whether proxy responses tend to improve agreement between the pair members. Table 8 shows the 

agreement among pairs with at least one proxy respondent compared with no proxy respondents, by pair type. For 

every pair type, the agreement is higher, usually much higher, for pairs with at least one proxy respondent. Pair types 

with high levels of agreement in the previous table (Table 7) are the pair types that tend to use proxies frequently: 

namely, the pairs with children aged 12 to 17. 

Table 8. Influence of Proxy Respondents on Agreement by Pair Type among Responding Pairs for Family 

Finer Categories Income: 2014 NSDUH 

Pair Type 

Responding Pairs Percent Agreement among Pairs 

Number 

Percent with at 

Least One 

Proxy 

At Least One 

Proxy No Proxies 

Parent-Child, Child Aged 12-14 2,596 97.34 77.92 68.12 

Parent-Child, Child Aged 15-17 2,139 92.01 79.98 50.88 

Parent-Child, Child Aged 18-20 711 49.93 75.49 44.38 

Parent-Child, Child Aged 21+ 790 30.25 78.66 46.64 

Parent-Child Total 6,236 81.61 78.58 47.86 

Sibling-Sibling, 12-14/15-17 1,291 98.22 85.02 56.52 

Sibling-Sibling, 12-17/18-25 1,330 91.05 66.31 35.29 

Sibling-Sibling, Other 1,543 69.09 80.21 37.11 

Sibling-Sibling Total 4,164 85.13 77.18 37.48 

Spouse-Spouse with Children 1,631 20.48 74.55 51.97 

Spouse-Spouse without Children 1,511 16.68 75.79 54.88 

Spouse-Spouse, Children Not Clear 22 4.55 100.00 42.86 

Spouse-Spouse Total 3,164 18.55 75.13 53.32 

Grandparent-Grandchild 193 75.65 60.96 44.68 

Overall Total 13,757 68.09 77.56 49.57 

Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 

2014. 

These results suggest that consistency would be increased by having only one member of the household respond to 

the family income questions, but this may not increase the accuracy of the family income measures. The next logical 

next step would be to use the pair data to estimate the measurement error. The family income questions are among 

the few NSDUH questions that are asked of two individuals who should be giving the same response. For these 

variables, it is probably true that the measurement error is larger than the sampling error. 

3.3 Promising Potential of Introducing Nonresponse-Specific Probe Items 

The final recommended next step for further reducing income item nonresponse is to explore the addition of probe 

items to the questionnaire. 

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There is evidence from drug measures in NSDUH that the inclusion of probe items asking for coarser estimates has 

some impact on nonresponse. Past month users of certain drugs are asked to report the number of days in the past 30 

days in which they have used the drug, and the resulting measure is referred to as 30-day frequency of use. If they 

respond "Don't know" or refuse this question, they receive a probe asking for an estimate of their drug use within the 

past 30 days from the following categories: 

• 1 or 2 days; 

• 3 to 5 days; 

• 6 to 9 days; 

• 10 to 19 days; 

• 20 to 29 days; and 

• all 30 days. 

The 30-day frequency-of-use probe questions have surprisingly high response rates, often greater than 80 percent 

(Table 9). If this approach is applied to income, perhaps the probe would include response levels matching the 

categories of the INCOME5 variable (Table 3), or even the levels of the POVERTY2 variable, based on the age and 

the responses to the household roster questions (Section 3.1.2). 

Table 9. Item Response Rates of 30-Day Frequency Probe Questions: 2014 NSDUH 

Drug 

Number of 

Nonrespondents to Original 

30-Day Frequency Question 

Number of 

Respondents to Probe 

Response Rate 

to Probe 

Cigarettes 103 94 91.26 

Snuff 20 16 80.00 

Chewing Tobacco 14 11 78.57 

Cigars 28 26 92.86 

Alcohol 234 196 83.76 

Inhalants 14 11 78.57 

Marijuana 81 69 85.19 

Hallucinogens 4 3 75.00 

Cocaine 1 1 100.00 

Crack 1 1 100.00 

Heroin 1 1 100.00 

Source: SAMHSA, Center for Behavioral Health Statistics and Quality, National Survey on Drug Use and Health, 

2014. 

Because it has been established that there are fundamental differences between nonresponse types, the current 

unfolding bracket structure of the NSDUH income questions could be improved by adding probe items based on 

types of nonresponse (i.e., “Don’t know” and refusals). Based on the understanding of cognitive factors surrounding 

income item nonresponse, it is recommended that the probe item for nonrespondents answering “Don’t know” 

should emphasize the reduction of response burden and help respondents come to a reasonable estimate. 

Furthermore, the probe item for nonrespondents refusing to answer the income items should focus on reassuring the 

respondent of anonymity and the importance in the accuracy of the survey estimates. The next step for examining 

the effectiveness of such probes in reducing income item nonresponse would require further refinement and field 

testing. 

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