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Bayesian sample‐size determination for inference on two binomial populations with no gold standard classifier
Author(s) -
Stamey James D.,
Seaman John W.,
Young Dean M.
Publication year - 2005
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.2167
Subject(s) - statistics , sample size determination , inference , bayesian probability , gold standard (test) , computer science , confidence interval , mathematics , econometrics , artificial intelligence
We consider the impact of test properties on the required sample size for the Bayesian design problem for comparing two proportions with error‐prone data. Specifically, we examine four cases: a single diagnostic test and two independent diagnostic tests, both when the test properties are identical across populations and when they differ. Interval‐based and moment‐based sample‐size determination criteria are contrasted using Monte Carlo simulation methods. We consider an application in which Strongyloides infections are compared in two populations. Copyright © 2005 John Wiley & Sons, Ltd.