Sample size determination for logistic regression: A simulation study

Bush, S

Sample size determination for logistic regression: A simulation study

Bush, S

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Publication Type:: Journal Article
Citation:: Communications in Statistics: Simulation and Computation, 2015, 44 (2), pp. 360 - 373
Issue Date:: 2015-01-01

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Field	Value	Language
dc.contributor.author	Bush, S https://orcid.org/0000-0003-2819-5412	en_US
dc.date.issued	2015-01-01	en_US
dc.identifier.citation	Communications in Statistics: Simulation and Computation, 2015, 44 (2), pp. 360 - 373	en_US
dc.identifier.issn	0361-0918	en_US
dc.identifier.uri	http://hdl.handle.net/10453/36250
dc.description.abstract	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. © 2015 Taylor & Francis Group, LLC.	en_US
dc.relation.ispartof	Communications in Statistics: Simulation and Computation	en_US
dc.relation.isbasedon	10.1080/03610918.2013.777458	en_US
dc.subject.classification	Statistics & Probability	en_US
dc.title	Sample size determination for logistic regression: A simulation study	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	44	en_US
utslib.for	0104 Statistics	en_US
utslib.for	01 Mathematical Sciences	en_US
utslib.for	08 Information and Computing Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	open_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	44	en_US

Abstract:

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. © 2015 Taylor & Francis Group, LLC.

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http://hdl.handle.net/10453/36250