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BMC Medical Research Methodology
Published in: BMC Medical Research Methodology 1/2015

Open Access 01-12-2015 | Research article

Sample size calculations for skewed distributions

Authors: Bonnie Cundill, Neal DE Alexander

Published in: BMC Medical Research Methodology | Issue 1/2015

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Abstract

Background

Sample size calculations should correspond to the intended method of analysis. Nevertheless, for non-normal distributions, they are often done on the basis of normal approximations, even when the data are to be analysed using generalized linear models (GLMs).

Methods

For the case of comparison of two means, we use GLM theory to derive sample size formulae, with particular cases being the negative binomial, Poisson, binomial, and gamma families. By simulation we estimate the performance of normal approximations, which, via the identity link, are special cases of our approach, and for common link functions such as the log. The negative binomial and gamma scenarios are motivated by examples in hookworm vaccine trials and insecticide-treated materials, respectively.

Results

Calculations on the link function (log) scale work well for the negative binomial and gamma scenarios examined and are often superior to the normal approximations. However, they have little advantage for the Poisson and binomial distributions.

Conclusions

The proposed method is suitable for sample size calculations for comparisons of means of highly skewed outcome variables.
Appendix
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Metadata
Title
Sample size calculations for skewed distributions
Authors
Bonnie Cundill
Neal DE Alexander
Publication date
01-12-2015
Publisher
BioMed Central
Published in
BMC Medical Research Methodology / Issue 1/2015
Electronic ISSN: 1471-2288
DOI
https://doi.org/10.1186/s12874-015-0023-0

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Erratum to: Correspondence: Some general points regarding Ledberg and Wennberg, BMC Medical Research Methodology 2014 April 27;14:58