Estimation and sample design in prevalence surveys of dementia.
Population prevalence rates of dementia using stratified sampling have previously been estimated using two methods: standard weighted estimates and a logistic model-based approach. An earlier study described this application of the model-based approach and reported a small computer simulation comparing the performance of this estimator to the standard weighted estimator. In this article we use large-scale computer simulations based on data from the recently completed Kame survey of prevalent dementia in the Japanese-American residents of King County, Washington, to describe the performance of these estimators. We found that the standard weighted estimator was unbiased. This estimator performed well for a sample design with proportional allocation, but performed poorly for a sample design that included large strata that were lightly sampled. The logistic model-based estimator performed consistently well for all sample designs considered in terms of the extent of variability in estimation, although some modest bias was observed.
Edland
S D
SD
Department of Environmental Health, University of Washington, Seattle 98195-4691, USA.
Graves
A B
AB
McCormick
W C
WC
Larson
E B
EB
D000368:Aged; D000369:Aged, 80 and over; D001213:Asian / Q000706:statistics & numerical data; D003704:Dementia / Q000453:epidemiology* / Q000208:ethnology; D006801:Humans; D007564:Japan / Q000208:ethnology; D016015:Logistic Models; D008875:Middle Aged; D009010:Monte Carlo Method; D011159:Population Surveillance; D015995:Prevalence; D012107:Research Design; D018401:Sample Size; D014861:Washington / Q000453:epidemiology