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A simple method of sample size calculation for linear and logistic regression
Author(s) -
Hsieh F. Y.,
Bloch Daniel A.,
Larsen Michael D.
Publication year - 1998
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(19980730)17:14<1623::aid-sim871>3.0.co;2-s
Subject(s) - logistic regression , statistics , sample size determination , mathematics , linear regression , sample (material) , logistic model tree , variance (accounting) , regression analysis , econometrics , chemistry , accounting , chromatography , business
A sample size calculation for logistic regression involves complicated formulae. This paper suggests use of sample size formulae for comparing means or for comparing proportions in order to calculate the required sample size for a simple logistic regression model. One can then adjust the required sample size for a multiple logistic regression model by a variance inflation factor. This method requires no assumption of low response probability in the logistic model as in a previous publication. One can similarly calculate the sample size for linear regression models. This paper also compares the accuracy of some existing sample‐size software for logistic regression with computer power simulations. An example illustrates the methods. © 1998 John Wiley & Sons, Ltd.