Dear Yi, On Wed, 31 May 2017 04:53:25 +0000 (UTC) array chip via R-help <r-help@r-project.org> wrote:
> Hi, I am running a logistic regression on a simple dataset (attached) > using glm: [...] As you can see, the interaction term is very > insignificant (p = 0.996)! Well, all terms are not significant (actually, AFAIK, the phrase "very insignificant" does not exist; and if it does, than it ought not). But look at the estimates and the standard errors too (might be easier if you had formatted your e-mail in a way that was readable)! What does an estimate for the intercept of 19.57 on the linear predictor scale mean? What it the estimated probability if you transform back? Perhaps the following command R> xtabs(~x1+x2+y,dat) will shed some more light on what is going on in your data set, and why the interaction term is highly significant. > But if I use a anova() to compare a full > vs reduced model to evaluate the interaction term: > > anova(glm(y~x1+x2,dat,family='binomial'), > > glm(y~x1*x2,dat,family='binomial')) To you know about the (optional) argument 'test="ChiSq"' for the anova() command if you use it to compare models fitted by glm()? (see help(anova.glm)) > So I get very different p value on the interaction term, can someone > share what's going wrong here? Data separation, aka Hauck-Donner phenomenon, discussed in any good book on logistic regression. Best wishes, Berwin ========================== Full address ============================ A/Prof Berwin A Turlach, Director Tel.: +61 (8) 6488 3338 (secr) Centre for Applied Statistics +61 (8) 6488 3383 (self) School of Maths and Stats (M019) FAX : +61 (8) 6488 1028 The University of Western Australia 35 Stirling Highway e-mail: berwin.turl...@gmail.com Crawley WA 6009 http://staffhome.ecm.uwa.edu.au/~00043886/ Australia http://www.researcherid.com/rid/A-4995-2008 ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.