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

From: <johnson4_at_babel.ling.upenn.edu>
Date: Sat, 01 Mar 2008 21:00:59 -0500


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 always slightly smaller.

anova() calculates the p-value based on "Chi-Square", but I have independent evidence that "Model L.R." is the actual -2*log(LR), so should I be using that?

Why are the values different?

prob_a <- inv.logit(rnorm(1,0,1))
prob_b <- inv.logit(rnorm(1,0,1))
data <- data.frame(
factor=c(rep("a",500),rep("b",500)),
outcome=c(sample(c(1,0),100,replace=T,prob=c(prob_a,1-prob_a)),

          sample(c(1,0),100,replace=T,prob=c(prob_b,1-prob_b)))) fit <- lrm(outcome~factor,data)

fit # gives "Model L.R." e.g. 8.23, 11.76, 6.89... anova(fit) # gives "Chi-Square" e.g. 8.19, 11.69, 6.85...

Previous Next | Save | Delete | Reply |



R-help_at_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. Received on Sun 02 Mar 2008 - 02:04:03 GMT

Archive maintained by Robert King, hosted by the discipline of statistics at the University of Newcastle, Australia.
Archive generated by hypermail 2.2.0, at Sun 02 Mar 2008 - 05:30:18 GMT.

Mailing list information is available at https://stat.ethz.ch/mailman/listinfo/r-help. Please read the posting guide before posting to the list.

list of date sections of archive