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 at 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