Solved – binary logit regression – which test apply for detecting heteroskedasticity

After reading a lot of different papers and a lot of different posts on the internet I still don't have a clue how to test on heteroskedasticity with my logistic regression (binary). The White test works only for OLS regression right?

Heteroscedasticity as such is not the main worry in logistic regression. For count data, the concern is overdispersion. The logistic model assumes that the probability of "success" is given by the model … but what if the probability of success is, say, a Beta random variable whose mean is your model mean? The expected counts would no longer be what the logistic predicts.

You could check for this possibility by fitting a beta-binomial model to see if the fit was substantially better — See R package bbmle.

To me, I would only go that route if I had subject matter grounds for modeling the success probability that way.

Overdispersion can also happen with Poisson counts.

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