Testing goodness-of-fit for logistic regression

TL;DR

This paper emphasizes the importance of including all relevant variables when testing the goodness-of-fit for logistic regression models, as it significantly enhances the test's statistical power.

Contribution

It introduces a method that explicitly accounts for all applicable variables, improving the effectiveness of goodness-of-fit tests in logistic regression.

Findings

Including all relevant variables increases test power substantially.

The proposed approach outperforms traditional methods in detecting model misfit.

Enhanced testing accuracy leads to better model validation.

Abstract

Explicitly accounting for all applicable independent variables, even when the model being tested does not, is critical in testing goodness-of-fit for logistic regression. This can increase statistical power by orders of magnitude.