Premium
Optimal predictive sample size for case–control studies
Author(s) -
Santis Fulvio De,
Pacifico Marco Perone,
Sambucini Valeria
Publication year - 2004
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/j.1467-9876.2004.0d490.x
Subject(s) - odds ratio , sample size determination , statistics , context (archaeology) , inference , epidemiology , medicine , econometrics , mathematics , computer science , artificial intelligence , biology , paleontology
Summary. The identification of factors that increase the chances of a certain disease is one of the classical and central issues in epidemiology. In this context, a typical measure of the association between a disease and risk factor is the odds ratio. We deal with design problems that arise for Bayesian inference on the odds ratio in the analysis of case–control studies. We consider sample size determination and allocation criteria for both interval estimation and hypothesis testing. These criteria are then employed to determine the sample size and proportions of units to be assigned to cases and controls for planning a study on the association between the incidence of a non‐Hodgkin's lymphoma and exposition to pesticides by eliciting prior information from a previous study.