I am trying to create a coefficient plot from multiple logistic regression models, which all have the same predictors, but different sample sizes. This is a pre-test to a multilevel model. My question is two fold:
Given, I want to compare the effect sizes of the same predictor in the different models, I assume I need to use standardized coefficients. How does one calculate standardized coefficients in a logit model?
Is there an easy way to estimate such coefficients in R? For instance with OLS, I could rely on the "lm.beta" function from the QuantPsyc package. I am wondering, is there a functional equivalent for a glm logit? I could not find an immediate solution myself.