On Moving to the Use of a Hybrid Sampling Frame in the National 

Survey on Drug Use and Health: Motivations and Challenges

Arthur Hughes1, Jonaki Bose1, Bonnie Shook-Sa2, and Katherine Morton2 

1. Substance Abuse and Mental Health Services Administration, 1 Choke Cherry Road Rockville, MD 20857

2. RTI International, 3040 Cornwallis Road, Research Triangle Park, NC 27709

Abstract

The sampling frame currently used in the National Survey on Drug Use and Health (NSDUH) is 

constructed by Listers who visit each selected area segment and conduct a complete enumeration of 

dwelling units that are eligible for selection. The half-open interval (HOI) procedure is used by Field 

Interviewers during the data collection phase to identify and include dwelling units that were missed 

during the listing operation. The use of Address-Based sampling (ABS) is increasingly becoming a viable 

alternative to traditional approaches for developing sampling frames and has the potential to significantly 

reduce costs associated with the listing operation. ABS relies solely on the use of a computerized listing 

of addresses (maintained and updated by the U.S. Postal Service) instead of field enumerated listings to 

select samples of dwelling units. 

Research was conducted recently to evaluate the coverage, cost, and implementation of a hybrid sampling 

frame for NSDUH, where ABS would be employed in most area segments while the traditional listing 

method would continue in areas where ABS coverage is low. A new Check for Housing Units Missed 

(CHUM) procedure was proposed to identify missed dwelling units to serve as a replacement for the HOI.

This conference paper will summarize the current NSDUH sample design including the sampling frame 

procedure, present a potential alternative hybrid sampling frame based on prior research, and discuss 

motivations, challenges, and current decisions associated with implementing a hybrid frame in NSDUH.

Keywords: Address-Based Sampling, hybrid frame, coverage, in-person surveys

Introduction 

Federal household surveys currently face a number of significant challenges including declining response 

rates and increasing costs of data collection (National Research Council, 2011). To combat increasing 

costs, the use of Address-Based Sampling (ABS) was investigated as an alternative to the use of 

traditional Field Enumeration (FE) methods in National Survey on Drug Use and Health (NSDUH) 

sampled area segments where the coverage of the target population was high. The use of FE in area 

segments would continue to be used in areas where coverage was low, all leading to the proposed 

construction of a hybrid sampling frame for NSDUH. Ideally, a hybrid frame consisting of a combination 

of ABS and FE segments would reduce survey costs compared to an FE-only frame without any loss in 

coverage of the target population. 

2005-2013 NSDUH Sample Design

The National Survey on Drug Use and Health (NSDUH) is a primary source of statistical information on 

use of illicit drugs, alcohol, tobacco, and mental health problems among the U.S. civilian non-institutional 

population aged 12 or older. It is sponsored by the Substance Abuse and Mental Health Services 

Administration (SAMHSA), U.S. Department of Health and Human Services, and is planned and 

managed by SAMHSA's Center for Behavioral Health Statistics and Quality (CBHSQ). Data collection 
and analysis are conducted under contract with RTI International. NSDUH is an ongoing survey that 

administers a variety of questions on substance use and associated behaviors in a face-to-face setting via 

computer-assisted interviewing at the respondents’ place of residence. 

The 2005-2013 NSDUH sample design and data collection was carried out as follows: 

 

1. stratify each State and the District of Columbia into a specified number of regions of approximately 

equal population, 

2. select census tracts within regions,

3. select area segments (consisting of a collection of adjacent census blocks) within selected tracts,

4. field enumerate all dwelling units (DUs) within sampled area segments, 

5. select dwelling units (DUs) within sampled area segments, 

6. screen each sampled DU in person by collecting roster data and selecting 0, 1, or 2 persons, and 

7. conduct an in-person interview with each selected person. 

The within-state stratification and selection of census tracts and area segments in steps 1, 2 and 3 were

completed well in advance of data collection using data available electronically from the U.S. Census 

Bureau and other sources. Each segment in step 3 consists of a set of adjacent census blocks that, in 

combination, satisfy the minimum requirement of 100 DUs in rural areas or 150 DUs in urban areas. This 

minimum number was determined to ensure that there would be a sufficient number of eligible DUs and 

subsequent completed interviews. Field Enumeration (FE) of DUs is completed by NSDUH field staff 

called “Listers” who physically travel to each sampled segment to manually count and list all DUs. This 

information is hand written on a segment listing form and provided to statisticians who select a sample of 

DUs.

Field interviewers visit sampled DUs in person where they use their hand-held computers to select 0, 1, or 

2 persons for the NSDUH interview. Before the interviewer leaves the sampled DU, she/he asks the 

screening respondent the following question: 

Are there any other living quarters within this structure or on this property, such as a separate apartment 

with a separate entrance?

Any such living quarters identified by the screening respondent are added to the sample. In addition, the

half-open interval (HOI) frame-linking procedure (Kish, 1965) is used to identify and add units that may 

not have been included on the frame by the Lister. Currently, NSDUH Interviewers are trained on using 

area segment maps and lists, and following the correct path of travel so they can implement HOI while in 

the field conducting screening and interviewing. The HOI states that if a dwelling unit is selected and an 

interviewer observes any new or missed dwelling units between the sample dwelling unit (SDU) and the 

dwelling unit appearing right after the SDU on the segment listing form, then all new or missed dwelling 

units between the SDU and the next dwelling unit on the listing form will be selected. The HOI is a 

standard procedure used by survey researchers and practitioners to reduce bias in survey estimates 

introduced by list frame undercoverage.

More details about the 2005-2013 sample design can be found in the NSDUH Sample Design Report 

(Morton et al, 2012).

 

2014 NSDUH Sample Design 

Faced with the need to update and improve the NSDUH survey on a variety of fronts, a new sample 

design was implemented beginning in 2014 followed by a redesigned questionnaire in 2015. Details about 
the 2014 design are provided in the 2014 NSDUH Office of Management and Budget (OMB) clearance 

materials (OMB, 2013). The new sample design includes the use of larger cluster sizes in some States and 

changes to the sample allocation by State and age leading to improved precision of most national 

estimates. Beginning in 2014 the HOI procedure was dropped. Dropping HOI was justified because a 

very small percentage of dwelling units are picked up by this method. In fact, of all added DUs in the 

fourth quarter of 2010 (a total of 381 added DUs), 272 (71.4 percent) were added as a result of the 

interviewer asking the screening respondent about additional units within or on the property of the SDU. 

The remaining 109 added DUs were found within the HOI and were usually either new construction or 

missed during the FE process. This implies that identifying missed units based solely on HOI accounted 

for only 0.2 percent of all 48,568 SDUs selected for the quarter. There are advantages to eliminating the 

HOI from the NSDUH. For example, FIs would no longer need to be trained on the path of travel so that 

portion of the training can be eliminated. It would also simplify the preparation of the field materials 

because there would be little need to generate a list of SDUs along with the next listed dwelling unit. 

However, FIs would still need to carry their segment maps and lists with them while in the field during 

screening and interviewing as they would be needed to locate the segments and dwelling units. 

To accommodate the potential use of ABS in future NSDUHs (i.e., after 2014), the 2014 design includes 

the selection of census block groups after the selection of census tracts. This additional stage of selection 

was included in order to reduce geocoding error in ABS segments since ABS segments would be 

geocoded for sampling purposes and to help interviewers locate the DU sample. Results from a NSDUH 

mailing list study field test showed that 89.9 percent of addresses from ABS frame geocoded into the 

correct area segment. However, 99.3 percent of those same addresses geocoded into the correct census 

block group. Compared to geocoding at the area census block level, geocoding accuracy improves 

significantly at the census block group level in both rural and urban areas. Thus, in an ABS design, it was 

determined that census block groups would serve as geographic clusters in areas with sufficient mailing 

address coverage. Since the use of census block groups as ABS segments will result in larger land areas, 

the within segment intraclass correlation is expected to decrease.

Address-Based Sampling

ABS in the household survey setting involves the use of mailing lists obtained from a database with 

(ideally) complete coverage of residential addresses that are eligible for selection. The primary source of 

these mailing lists is the Computerized Delivery Sequence (CDS) file maintained by the U.S. Postal 

Service (USPS, 2011) and made available to the public through licensing agreements with qualified 

vendors. The CDS file includes locatable city-style addresses consisting of a street number and name, 

city, state, and nine-digit ZIP Code for approximately 96 percent of unique residential addresses1

 on the 

file (Iannacchione 2011). No names are associated with this file. Examples of survey organizations that 

use the CDS are: the U.S. Census Bureau for updating their Master Address File which in turn is used as a 

sampling frame in a number of household surveys including the American Community Survey (U.S. 

Census Bureau, 2011) and the National Center for Health Statistics which use the CDS to update the 

sampling frame for the National Survey of Family Growth (Lepkowski et al, 2010). 

 

Similar to conducting HOI on FE area segments, procedures to identify and add missed units in ABS

segments may be needed. Such procedures are provided below. 

1 This estimate excludes PO Box addresses that are not the residents’ only way to receive mail.

 
Identification of Missed Addresses in ABS

Cost savings are the primary advantage of using ABS over FE for in-person surveys of the civilian, noninstitutionalized population. However, prior research indicates that ABS coverage of the household 

population is incomplete, especially in rural areas (Iannacchione et al. 2010). A hybrid sampling frame 

was developed for the NSDUH with the goal of lowering costs without sacrificing coverage levels of the 

current FE sampling frame. Using an expected ABS coverage rate, segments with a coverage rate at or 

above a predetermined coverage threshold will use ABS supplemented with the Check for Housing Units 

Missed (CHUM) frame-linking procedure to identify and record DUs that are not included on the ABS 

list (McMichael et al. 2008). All other segments will be scheduled for FE supplemented with the halfopen interval (HOI) frame-linking procedure (Kish 1965). 

The CHUM procedure is designed to be used in segments where ABS coverage is adequate but not 

complete. As Figure 1 demonstrates, the CHUM procedure uses two components to supplement the 

coverage of an ABS frame. The CHUM1 component enables FIs to establish a path of travel from the 

sampled DU to the "next DU." This methodology requires segments with discernible boundaries so that 

DUs can be identified as being within a sampled segment. Facing the located sampled DU, the FI travels

clockwise around the block, without crossing a street to find the next DU. Street crossings are avoided to 

ensure that each path of travel is non-overlapping.

Figure 1: Examples of CHUM Components

Path of travel

DU not on ABS frame

DU on ABS frame

17th St Gatewood Ave

Indiana Ave

15th St

N

START

1

3 2

Indiana Ave

16th St

CHUM1

Component

CHUM2

Component

Blackwater Ave

CHUM1 Component: Path of travel moves clockwise from the selected DU. If DU 1 is selected, one 

missed DU would be added to the ABS frame. If DU 2 is selected, two missed DUs would be added. No 

missed DUs would be added if DU 3 is selected. CHUM2 Component: First, a block or area is randomly 

selected within a segment. Then, FIs are provided a segment map that enables the entire block to be field 

enumerated. In this case, three missed DUs are added to the frame. Notice that the three missed DUs have 

no chance for inclusion solely using CHUM1. 
After the address of the next DU is found, it is checked against the ABS frame to determine whether it 

was missed. This check requires access to the entire ABS frame within each selected segment. If the 

address of the next DU is not on the ABS frame, the DU is sampled and assigned a probability of

selection that is linked to the probability of selecting the sampled DU. If multiple missed DUs are picked 

up by the CHUM1, then subsampling may be used to control the sample size. Otherwise, a missed DU 

will be included in the sample and assigned the same design weight as the sampled DU. This step is 

repeated until either the address of a DU on the ABS frame is found or the block is circumnavigated. 

Because CHUM1 is restricted to blocks associated with a sampled address, DUs in blocks with no 

addresses on the ABS frame will be missed. CHUM2 mitigates this source of undercoverage by adding 

the "missed blocks" and their associated DUs to the frame. For segments that contain multiple missed 

blocks, efficient sampling methods can be used to select a subsample of missed DUs.

In addition to employing the CDS file and implementing a missed DU procedure such as the CHUM, the 

U.S. Postal Service also provides a supplemental address file that has the potential for increasing 

coverage. It is called the No-Stat file and is discussed next. 

Expanding the Coverage of ABS with the No-Stat File

Address-based sampling frames are traditionally based on the USPS CDS file, which USPS makes 

available to qualified vendors through nonexclusive licensing agreements. Since 2009, USPS has also 

made available the No-Stat file, which supplements the CDS file with approximately seven million 

predominantly rural addresses not found on the CDS file. 

The No-Stat file is a supplemental file also maintained by the U.S. Postal Service that contains addresses 

that are classified as inactive or that are not currently receiving mail delivery at their household. 

Examples of these addresses are new housing developments, rural delivery points that have been vacant 

for 90 days or longer and gated communities that do not receive delivery by USPS personnel to individual 

units (USPS, 2011). 

An evaluation of the No-Stat file based on 2010 NSDUH data found that it includes the addresses of 

approximately 1.3 million occupied housing units and provides household coverage gains of 1.2 percent 

overall and 3.8 percent in rural areas. While these coverage gains are modest, including the No-Stat file is 

a cost effective strategy for boosting rural coverage because its inclusion does not significantly reduce the 

efficiency of the ABS frame (Shook-Sa et al. in press).

Hybrid Sampling Frame

Iannacchione et al. (2010) evaluated the feasibility of implementing a hybrid sampling frame based on a 

probability sample of 200 segments and 3,878 eligible dwelling units (DUs) from the NSDUH. Here, a 

hybrid frame is defined as one where area segments are classified into FE and ABS to maximize coverage

while reducing costs and interviewer burden. Various ABS coverage thresholds were evaluated in terms 

of cost savings and coverage. As the ABS coverage threshold decreases, fewer segments rely on FE and, 

therefore, the estimated cost savings increases (Table 1). As shown in Table 2, there is not much 

difference in DU coverage in urban segments. However, there is a mild increase in coverage of rural DUs 

at higher ABS coverage thresholds. Theoretically, the hybrid sampling frame should provide 100% 

coverage of the target population. However, as with any frame supplementation method, a loss of 

coverage occurs when field interviewers neglect to follow the correct protocols when implementing the 

CHUM procedures. 
Table 1: Estimated Annual Cost Savings1

 of the Hybrid Frame 

ABS Coverage 

Threshold2

FE Segments ABS Segments Estimated 

3 Cost Savings # % # % 

20% 384 5.5% 6,624 94.5% 62.3% 

50% 1,076 15.4% 5,932 84.6% 55.4% 

80% 2,565 36.6% 4,443 63.4% 40.1% 

FE Only 7,008 100.0% 0 0.0% 0.0% 

ABS = address-based sampling; FE = field enumeration. 

1 Cost savings include costs incurred after the selection of the segment and before the start of field interviewing. Costs include 

the half-open interval (HOI) for FE segments and the Check for Housing Units Missed (CHUM) for ABS segments. Excluded 

are the costs associated with the 192 NSDUH segments in Alaska and Hawaii.

2 Ratio of the number of city-style mailing addresses in a segment to the Census Bureau/Claritas dwelling unit (DU) estimate.

3 Compared with doing FE in all segments.

Table 2: Estimated Coverage of NSDUH Dwelling Units of the Hybrid Frame

ABS Coverage Threshold 

20% 50% 80% 

Urban Segments 98.9% 99.0% 99.1% 

Rural Segments 92.3% 93.4% 95.6% 

Overall 97.5% 97.8% 98.4% 

How closely the estimated ABS coverage comes to predicting the actual ABS coverage greatly influences 

cost and coverage. By accurately predicting ABS coverage, low coverage segments will always be field 

enumerated, and fewer segments with marginal ABS coverage will rely on the CHUM. Therefore, 

accurately predicting ABS coverage at the area-segment level prior to sample selection simultaneously 

lowers costs and improves frame coverage. Using the field study sample of 200 NSDUH segments, 

McMichael et al. (2010) compared predicted ABS coverage to actual ABS coverage. Using a coverage 

threshold of 50%, eighty-four percent of NSDUH segments were correctly allocated to the ABS frame 

and only one percent was incorrectly assigned to ABS. Similarly, seven percent of NSDUH segments 

were correctly allocated to FE but eight percent had sufficient ABS coverage and were incorrectly 

allocated to FE. Several of the segments that were incorrectly allocated to ABS when they should have 

been field enumerated had a high proportion of group quarters. Thus, information about the presence of 

group quarters in segments can be used to more accurately predict segment coverage and allocation to 

ABS or FE. (Figure 1)