I'm modeling (using GLM) one binary explanatory variable against a binary response variable.
The output looks ok to me, but I'm a biologist with a basic knowledge of stats, I just wanted to ask if there's any rule/caveat/problem for modeling a binary versus a binary?
Best Answer
In the general linear model the explanatory variables can be binary, categorical, discrete or continuous but the response variable is generally continuous. For a generalized linear model the explanatory variables can still be binary, categorical, discrete or continuous but applying the logit as the link function allows for the response variable to be binary too. So that is a longwinded way of saying in a generalized linear model you can have a binary explanatory variable with a binary response.