Sidra, I don't know of any specific programs, but the approach I have taken to doing logistic regression on paired observations is simply to do a logistic regression on the following two of the four possibilities for each pair: 1,0 and 0,1. You can disregard the 1,1 and 0,0 options, and the corresponding observations can be omitted from the analysis. This approach is based on the same principle that applies to chi-square tests of paired, non-independent samples (i.e., McNemar Asymmetry tests). Done this way, the analysis is just a simple logistic regression, wherein the 1,0 combination can be treated as one of the response categories and the 0,1 combination as the other.
I'm sure there will be some statistical hotshots on the forum who will criticize this approach and have better (more sophisticated) suggestions, but this approach seems reasonable to me and is familiar and easy to understand. Good luck, Steve Brewer ________________________________________ From: Ecological Society of America: grants, jobs, news [[email protected]] on behalf of Sidra Blake [[email protected]] Sent: Friday, December 09, 2011 3:08 PM To: [email protected] Subject: [ECOLOG-L] Paired Logistic Regression for Resource Selection Ecologgers, I wondered if any eco-statters could provide their opinion in statistics if they don't mind. I require a statistical program that conducts matched (paired) logistic regression , which I believe is equivalent to conditional logistic regression (case-control) for a resource selection study. Most of the ecological papers that use this statistical approach cite STATA or other software that I , nor any local lab I know of, do not have licenses for. I have not seen anyone cite R for this approach in the literature I consult. And online I am unable to find examples, in R, that are in similar context to my own data. I live and learn from examples via scientific literature and online code examples, so I am a bit discouraged at this point, hung up I guess. However, conditional logistic regression does appear possible in R, from one source I found online via the survival package. Though, that example was very limited in depth. This leads me to a few questions. 1) What are my statistical software options for matched logistic regression (with categorical and continuous data) - and which do users seem to prefer? 2) Has anyone used R for this statistical approach? 3) And, has anyone been able to incorporate random effects (or mixed effects see Duchesne et al. 2010) by the experimental unit (ie-individual) into this design? I admit I am new to logistic regression and resource selection analysis. This means, I would deeply benefit from detailed examples for this approach. I appreciate any feedback. Please feel free to email me off the listserve at the email address below, and please use the subject heading of this post. Thanks, Sidra Sidra Blake Land Management and Demonstration Program Mid-Columbia River NWRC US Fish and Wildlife Service MS Student Natural Resource Sciences Washington State University sidra.blakeATwsu.edu "We shall never achieve harmony with land, any more than we shall achieve absolute justice or liberty for people. In these higher aspirations, the important thing is not to achieve but to strive. " ~Aldo Leopold
