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

Preface
This report documents the method of weight calibration used for producing the final set
of questionnaire dwelling unit (QDU) and pair weights for the National Survey of Drug Use and
Health (NSDUH) data from 2006. The weighting team faced several challenges in this task and
was able to address them by resorting to innovative modifications of certain basic statistical
ideas. These are listed below.
• Under Brewer's method, high weights may occur due to small pair selection
probabilities. In any calibration exercise, some treatment of extreme value (ev) in
weights is needed, but there is a danger of introducing too much bias by overtreatment.
In the generalized exponential model (GEM), which is described in detail
in Chen et al. (2008), extreme value control is built in, but one needs to define
suitable ev domains so that not too many evs are defined. If too many design
variables are used to define ev domains, then each domain will be very sparse and
will not be of much use in defining thresholds for ev. As in past surveys, a hierarchy
of domains was defined using pair age (each pair member being in one of the three
categories: 12 to 25, 26 to 49, and 50+) and number of persons aged 12 to 25 in the
household, State, and clusters of States (see Section 5.2 for details).
• Control of extreme values in weights helps reduce instability of estimates to some
extent, but there is a need for methods that do not introduce much bias. Following the
famous suggestion of Hajek (1971) in his comments on Basu's fabled example of
circus elephants, we performed ratio adjustment (a form of poststratification) to
estimated totals obtained from the household data on the number of persons
belonging to the pair domain of interest. This was implemented in a multivariate
manner to get one set of final weights.
• In the absence of a suitable source of poststratification controls for the person pairlevel
weights and the household-level weights, the inherent two-phase nature of the
survey design was capitalized upon to estimate these controls from the first phase of
the large screener sample. The first-phase sample weight was poststratified to personlevel
U.S. Bureau of the Census counts to get more efficient estimated counts for pair
and household data.
• The problem of multiplicities complicated the issue of providing one set of final
weights. When dealing with person-level parameters involving drug-related behaviors
among members of the same household, it is possible for an individual to manifest
himself or herself in the pair sample through different pairs. To avoid overcounting,
the pair weights have to be divided by multiplicity factors, which tend to be domain
specific. For this reason, multiplicity factors for a key set of pair analysis domains
also are produced along with a set of final calibrated pair weights.
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