I'm running a logistic regression model in R. I've used both the Zelig and Car packages. However, I'm wondering if there is a simple way to get the model fit statistics for the model. (pseudo R-square, chi-square, log liklihood,etc)
summary() provides me with the coefficients and regression parameters. That's important, but not what I'm looking for.Furthermore, with the Zelig output, I get the following output: Null deviance: 1068.24 on 772 degrees of freedom Residual deviance: 939.48 on 761 degrees of freedom (941 observations deleted due to missingness) AIC: 963.48
Tony
2010-07-26 17:04:06
thanks!!! I also found that running the logistic regression using the lrm function from the Design package gives the pseudo-R^2 as an output.
Tony
2010-07-26 19:02:29
A:
It's hard to answer this question without knowing what the model object is. I'm not sure what Zelig produces.
I would look at names(model), names(summary(model)) or names(anova(model,test = "Chisq")) to see if the stats you want are there. I know that for log-likelihood, logLik(model) will give you what you want.
JoFrhwld
2010-07-26 17:49:24
A:
While I'm no expert, model fit statistics for logistics regression models are not as straightforward in their interpretation as those in linear regression. Assuming you have a binary response, one method I've found useful is to group your data by predicted probability interval (0-10%, 10%-20%,....90%-100%) and comparing the actual probabilities to the predicted ones. This is very helpful because often your model will over predict at the low end or under predict at the high end. This may lead to a better model as well.
Grembo
2010-07-29 19:27:08