Quoting Frank E Harrell Jr <[EMAIL PROTECTED]>: > anova (anova.Design) computes Wald statistics. When the log-likelihood > is very quadratic, these statistics will be very close to log-likelihood > ratio chi-square statistics. In general LR chi-square tests are better; > we use Wald tests for speed. It's best to take the time and do > lrtest(fit1,fit2) in Design, where one of the two fits is a subset of > the other. > > Frank Harrell
Thanks, this is great, but in my case, there's just one factor, fit1 <- lrm(outcome~factor,data) and I'm having trouble constructing the subset 'null model', as e.g. fit2 <- lrm(outcome~1,data) returns an error message. How do I construct a null model with lrm() so that I can use lrtest() to test a model with only one predictor? I apologize for asking what must be a very simple question but I have been unable to find the answer by searching R-help. Thanks, Dan P.S. Second point: I have another case where I use lmer(), and there the null model includes a random effect so I don't get the problem above. It looks like with lmer objects anova() uses LLR, not Wald. Is that right? ______________________________________________ R-help@r-project.org 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.
