title: Sample size to test for interaction between a specific exposure and a second risk factor in a pair-matched case-control study.
abstract: 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(A2) 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(A2) polymorphism and a second risk factor such as smoking status and homocysteine level. We introduce the algorithm in detail with several numerical examples.
authors.affiliation: School of Statistics, University of Minnesota, Minneapolis, MN 55455, USA. qiu@stat.umn.edu
authors.forename: P
authors.initials: P
authors.lastname: Qiu
authors.forename: M L
authors.initials: ML
authors.lastname: Moeschberger
authors.forename: G E
authors.initials: GE
authors.lastname: Cooke
authors.forename: P J
authors.initials: PJ
authors.lastname: Goldschmidt-Clermont
mesh_terms: D000465:Algorithms; D016022:Case-Control Studies; D003627:Data Interpretation, Statistical; D006710:Homocysteine / Q000378:metabolism; D006801:Humans; D009203:Myocardial Infarction / Q000209:etiology / Q000235:genetics; D011110:Polymorphism, Genetic; D012307:Risk Factors; D018401:Sample Size; D012907:Smoking / Q000009:adverse effects
chemical_list: D006710:Homocysteine