In a previous post we looked at the popular Hosmer-Lemeshow test for logistic regression, which can be viewed as assessing whether the model is well calibrated. In this post we’ll look at one approach to assessing the discrimination of a fitted logistic model, via the receiver operating characteristic (ROC) curve.
Jonathan Bartlett
Deviance goodness of fit test for Poisson regression
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.
Wilcoxon-Mann-Whitney as an alternative to the t-test
The two sample t-test is one of the most used statistical procedures. Its purpose is to test the hypothesis that the means of two groups are the same. The test assumes that the variable in question is normally distributed in the two groups. When this assumption is in doubt, the non-parametric Wilcoxon-Mann-Whitney (or rank sum ) test is sometimes suggested as an alternative to the t-test (e.g. the Wikipedia page on the t-test), which doesn’t rely on distributional assumptions. But is this necessarily a good ‘replacement’?