[R] strange results from binomial lmer?

d also compared to the glm() model with both fixed factors 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";)

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 spe

[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 i

[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 i