Conditional logistic regression: Difference between revisions

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'''Conditional logistic regression''' is an extension of [[logistic regression]] that allows one to take into account [[stratification (clinical trials)|stratification]] and [[Matching (statistics)|matching]]. Its main field of application is [[observational studies]] and in particular [[epidemiology]]. It was devised in 1978 by [[Norman Breslow]], [[Nick Day|Nicholas Day]], K. T. Halvorsen, [[Ross L. Prentice]] and C. Sabai.<ref name="pmid727199">{{cite journal|vauthors=Breslow NE, Day NE, Halvorsen KT, Prentice RL, Sabai C| title=Estimation of multiple relative risk functions in matched case-control studies. | journal=Am J Epidemiol | year= 1978 | volume= 108 | issue= 4 | pages= 299–307 | pmid=727199 | doi= 10.1093/oxfordjournals.aje.a112623| pmc= | url=https://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=sumsearch.org/cite&retmode=ref&cmd=prlinks&id=727199 }} </ref> It is the most flexible and general procedure for matched data.

==Motivation==

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==Implementation==

Conditional logistic regression is available in R as the function <code>clogit</code> in the <code>survival</code> package. It is in the <code>survival</code> package because the log likelihood of a conditional logistic model is the same as the log likelihood of a Cox model with a particular data structure.<ref>{{cite web |url=https://stat.ethz.ch/R-manual/R-devel/library/survival/html/clogit.html |title=R documentation Conditional logistic regression |last1=Lumley |first1=Thomas |date= |website= |publisher= |access-date=November 3, 2016}}</ref>

==Related tests==