Part I dealt with logit models with dichotomous (0/1) predictors. These are handy models, but usually we deal with predictors that are continuous. That’s the point of Part II, where I walk through making sense of these models, focusing especially on calculating and plotting marginal effects and predicted probabilities.

You can find a link to Part II on my resources page, or here:

Happy Memorial Day weekend, and thanks to all who serve and have served!

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