Sample size determination for logistic regression on a logit-normal distribution

Statistical Methods in Medical Research
Seongho KimLance Heilbrun

Abstract

Although the sample size for simple logistic regression can be readily determined using currently available methods, the sample size calculation for multiple logistic regression requires some additional information, such as the coefficient of determination ([Formula: see text]) of a covariate of interest with other covariates, which is often unavailable in practice. The response variable of logistic regression follows a logit-normal distribution which can be generated from a logistic transformation of a normal distribution. Using this property of logistic regression, we propose new methods of determining the sample size for simple and multiple logistic regressions using a normal transformation of outcome measures. Simulation studies and a motivating example show several advantages of the proposed methods over the existing methods: (i) no need for [Formula: see text] for multiple logistic regression, (ii) available interim or group-sequential designs, and (iii) much smaller required sample size.

References

Jul 1, 1989·Statistics in Medicine·F Y Hsieh
Aug 12, 1998·Statistics in Medicine·F Y HsiehM D Larsen
Dec 10, 1999·Controlled Clinical Trials·R Wolfe, J B Carlin
Jul 5, 2013·The Prostate·Jonathan E McDunnThomas M Wheeler

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Methods Mentioned

BETA
biopsy

Software Mentioned

R package pracma
R package
PASS
ssLogitNorm
R

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