In this post we’ll look at the deviance goodness of fit test for Poisson regression with individual count data. Many software packages provide this test either in the output when fitting a Poisson regression model or can perform it after fitting such a model (e.g. Stata), which may lead researchers and analysts in to relying on it. In this post we’ll see that often the test will not perform as expected, and therefore, I argue, ought to be used with caution.
Logistic regression / Generalized linear models
The Hosmer-Lemeshow goodness of fit test for logistic regression
Before a model is relied upon to draw conclusions or predict future outcomes, we should check, as far as possible, that the model we have assumed is correctly specified. That is, that the data do not conflict with assumptions made by the model. For binary outcomes logistic regression is the most popular modelling approach. In this post we’ll look at the popular, but sometimes criticized, Hosmer-Lemeshow goodness of fit test for logistic regression.