Estimation and sample design in prevalence surveys of dementia

J Clin Epidemiol. 1999 May;52(5):399-403. doi: 10.1016/s0895-4356(99)00003-7.


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.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Asian Americans / statistics & numerical data
  • Dementia / epidemiology*
  • Dementia / ethnology
  • Humans
  • Japan / ethnology
  • Logistic Models
  • Middle Aged
  • Monte Carlo Method
  • Population Surveillance
  • Prevalence
  • Research Design*
  • Sample Size
  • Washington / epidemiology