Visualizing Logistic Regression In Action

Sebastian Sauer shows using ggplot2 visuals what happens when there are interaction effects in a logistic regression:

Of course, probabilities greater 1 do not make sense. That’s the reason why we prefer a “bended” graph, such as the s-type ogive in logistic regression. Let’s plot that instead.

First, we need to get the survival probabilities:

d %>% mutate(pred_prob = predict(glm1, type = "response")) -> d

Notice that type = "response gives you the probabilities of survival (ie., of the modeled event).

Read the whole thing.

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