Abstract
Richard Valliant (1995) "Limitations
of Balanced Half Sampling," Proceedings of the Section on
Survey Research Methods, American Statistical Association.
Balanced half-sample (BHS) variance estimation is a
popular technique among survey statisticians, but it has
limitations. These limits are studied theoretically through a
model-based approach and illustrated with simulations using
artificial and real populations. In the fully balanced case,
under a model often used for stratified, clustered
populations, BHS produces a model-unbiased variance estimator
for only one member of a broad class of estimators of totals.
Another implementation of BHS variance estimation in large,
complex surveys is to use partial balancing or grouping of
strata to reduce the number of resample estimates that must
be calculated. Instead of selecting a fully balanced,
orthogonal set of half-samples, strata are combined into
groups and a set of half-samples only large enough to be
balanced on the groups is selected. For two-stage cluster
samples either with or without poststratification this leads
to an inconsistent variance estimator.
Last Modified Date: July 19, 2008
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