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Sample Size Determination for Logistic Regression: A Simulation Study

Stephen Bush
Organization: University of Technology Sydney
Department: School of Mathematical Sciences
Journal / Anthology

Communications in Statistics—Simulation and Computation
Year: 2015
Volume: 44
Page range: 360–373

Likelihood ratio test; Mathematica; Power; Score test; Wald test

This article considers the different methods for determining sample sizes for Wald, likelihood ratio, and score tests for logistic regression. We review some recent methods, report the results of a simulation study comparing each of the methods for each of the three types of test, and provide Mathematica code for calculating sample size. We consider a variety of covariate distributions, and find that a calculation method based on a first order expansion of the likelihood ratio test statistic performs consistently well in achieving a target level of power for each of the three types of test.

*Mathematics > Probability and Statistics