Hello,

I'm running a binary (2 groups), multivariate (multiple predictors) logistic regression analysis, and would like to test the classification rate.

In the case of a single predictor, calculating the classification rate of a logistic regression is fairly straight forward.

But, the addition of another predictor is equivalent to introducing another logistic function, right?

For example, see this pairwise plot of a 4 predictor regression:
http://alumni.media.mit.edu/~tpminka/courses/36-350.2001/lectures/day31/iris-plot1.png

In this case, the "threshold" for predicted group membership is more difficult to calculate. It seems that group membership should be calculated as some weighted sum of the individual logits. Where do I get the weightings? How do I calculate predicted group membership?

my thanks in advance.

You just have one outcome (yes/no, 1/0) and multiple regressions right? Then you just have ordinary logistic regression. Your mis-classifications rate (if that is what you meant) is the same regardless of the number of predictors (you still have a predicted class and an actual class).