[R] strange results from binomial lmer?

and no random factor ('gs'). This doesn't make much sense to me. I've placed a dataset on the Web that exhibits this behavior, as follows: dat - read.csv(http://www.ling.upenn.edu/~johnson4/strange.csv;) gs - glm(outcome~gender+stress,binomial,dat) g_s - lmer(outcome~gender+(1|speaker),dat,binomial) s_s

[R] difference between lrm's Model L.R. and anova's Chi-Square

I am running lrm() with a single factor. I then run anova() on the fitted model to obtain a p-value associated with having that factor in the model. I am noticing that the Model L.R. in the lrm results is almost the same as the Chi-Square in the anova results, but not quite; the latter value is

Re: [R] difference between lrm's Model L.R. and anova's Chi-Square

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.

[R] difference between lrm's Model L.R. and anova's Chi-Square

I am running lrm() with a single factor. I then run anova() on the fitted model to obtain a p-value associated with having that factor in the model. I am noticing that the Model L.R. in the lrm results is almost the same as the Chi-Square in the anova results, but not quite; the latter value is