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Sample size to test for interaction between a specific exposure and a second risk factor in a pair‐matched case‐control study
Author(s) -
Qiu Peihua,
Moeschberger Melvin L.,
Cooke Glen E.,
GoldschmidtClermont Pascal J.
Publication year - 2000
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/(sici)1097-0258(20000415)19:7<923::aid-sim341>3.0.co;2-o
Subject(s) - odds ratio , risk factor , logistic regression , sample size determination , statistics , case control study , logarithm , mathematics , odds , medicine , mathematical analysis
We discuss a sample size calculation for a pair‐matched case‐control study to test for interaction between a specific exposure and a second risk factor. The second risk factor could be either binary or continuous. An algorithm for the calculation of sample size is suggested which is based on a logistic regression model that relates the logarithm of the disease‐exposure odds ratio to the second risk factor. This problem is motivated by a study comparing the prevalence of GP‐IIIa Pl A 2 polymorphism (the exposure) in individuals with and without myocardial infarction (case‐control). One of the hypotheses in this study is whether or not there is an interaction between the prevalence of GP‐IIIa Pl A 2 polymorphism and a second risk factor such as smoking status and homocysteine level. We introduce the algorithm in detail with several numerical examples. Copyright © 2000 John Wiley & Sons, Ltd.