Edwin Commandeur wrote: > Dear all, > > I am comparing logistic regression models to evaluate if one predictor > explains additional variance that is not yet explained by another predictor. > As far as I understand Baron and Li describe how to do this, but my question > is now: how do I report this in an article? Can anyone recommend a > particular article that shows a concrete example of how the results from te > following simple modeling can be reported: > > glm1 = glm(DV ~ A, family = binomial) > glm2 = glm(DV ~ A + B, family = binomial) > anova(glm1, glm2, test = "Chisq") > > Any help on how this simple kind of modeling should be reported is > appreciated. > > Greetings, > Edwin Commandeur
There are many ways, including odds ratios and partial effect plots and Brier scores. For a pure likelihood measure I talk about an 'adequacy index' (adequacy of the smaller model) in my book, which was used in a medical paper: @ARTICLE{cal85, author = {Califf, R. M. and Phillips, H. R. and others}, year = 1985, title = {Prognostic value of a coronary artery jeopardy score}, journal = J Am Coll Cardiology, volume = 5, pages = {1055-1063} } Frank Harrell > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Frank E Harrell Jr Professor and Chair School of Medicine Department of Biostatistics Vanderbilt University ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.