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Inverse Sampling in Case Control Studies Involving a Rare Exposure
Author(s) -
Kikuchi David A.
Publication year - 1987
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.4710290222
Subject(s) - negative binomial distribution , statistics , covariate , sampling (signal processing) , logistic regression , mathematics , binomial distribution , binomial (polynomial) , macro , econometrics , computer science , poisson distribution , computer vision , programming language , filter (signal processing)
In case‐control studies where the outcome is not uncommon but the exposure is rare, inverse sampling may be used to reduce the total number of subjects required to find a fixed number of exposed cases and controls. The sampling distribution is negative binomial rather than binomial. Logistic regression for adjustment of covariates may be implemented on the computer program GLIM by the appropriate use of macros. An example is given.