Large sample convergence diagnostics for likelihood based inference: Logistic regression

摘要

A general diagnostic approach to the evaluation of asymptotic approximation in likelihood based models is developed and applied to logistic regression. The expected asymptotic and observed log likelihood functions are compared using a chi distribution in a directional Bayesian setting. This provides a general approach to assessing and visualizing non-convergence in higher dimensional models. Several well-known examples from the logistic regression literature are discussed. Crown Copyright (C) 2016 Published by Elsevier B.V. All rights reserved.