Questionnaire Dwelling Unit-Level and Person Pair-Level Sampling ...

7. Weight Calibration at Questionnaire
Dwelling Unit and Pair Levels
The 2006 National Survey on Drug Use and Health (NSDUH) was based on probability
sampling so that valid inferences can be made from survey findings about the target population.
Probability sampling refers to sampling in which every unit on the frame is given a known,
nonzero probability for inclusion in the survey. This is required for unbiased estimation of the
population total. The assumption of nonzero inclusion probability for every pair of units in the
frame also is required for unbiased variance estimation. The basic sampling plan involved four
stages of selection across two phases of design: within Phase I, (1) the selection of census tracts
within each State sampling (SS) region, (2) the selection of subareas or segments (comprised of
U.S. Bureau of the Census blocks) within SS regions; (3) the selection of dwelling units (DUs)
within these subareas; and, finally, within Phase II, (4) the selection of eligible individuals within
DUs. Specific details of the sample design and selection procedures for the sample can be found
in the 2006 NSDUH sample design report (Morton et al., 2007).
As part of the postsurvey data-processing activities, analysis weights that reflected the
selection probabilities from various stages of the sample design were calculated for respondents.
These sample weights were adjusted at the DU (screening sample), questionnaire dwelling unit
(QDU), person, and paired respondent levels (the latter three all based around the drug
questionnaire sample) to account for bias due to extreme values (ev), nonresponse (nr), and
coverage.
The final sample weights for Phase I screener dwelling units (SDU) and Phase II QDU,
person, and pair levels for the 2006 samples consisted of products of several factors, each
representing either a probability of selection at some particular stage or some form of ev, nr, or
ps calibration adjustment. In the following sections, we describe the QDU and pair weight
components in greater detail. In summary, the first 10 factors were defined for all SDUs and
reflected the fully adjusted SDU sample weight. The remaining components branched to reflect
QDU and pair selection probabilities, as well as additional adjustments for ev, nr, and ps. Note
that the final QDU and pair weights for the 2006 survey sample are the product of all weight
components for each type of sample, illustrated in Exhibits 7.1 and 7.2.
For QDU data, generalized exponential modeling (GEM) calibration modeling was
applied by partitioning the data into four groups of States: Northeast, South, Midwest, and West,
based on census regions in the interest of computational feasibility. Previous experience showed
that with current computing power, the large number of variables and records prevented any
further reduction of modeling groups.
For pair data, GEM modeling was initially applied by partitioning the pair data into four
groups based on census regions. However, there were not enough observations in each group to
fit a comprehensive model to reduce bias. Alternatively, a single model was attempted for the
whole pair data, but it was rejected as not practical due to computational limitations. A
compromise approach was adopted by combining census regions into two groups: Northeast with
South and Midwest with West. This grouping proved both manageable and desirable as it
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