title: Nonparametric Diagnostic Test for Conditional Logistic Regression.
abstract: The use of conditional logistic regression models to analyze matched case-control data has become standard in statistical analysis. However, methods to test the fit of these models has primarily focused on influential observations and the presence of outliers, while little attention has been given to the functional form of the covariates. In this paper we present methods to test the functional form of the covariates in the conditional logistic regression model, these methods are based on nonparametric smoothers. We assess the performance of the proposed methods via simulation studies and illustrate an example of their use on data from a community based intervention.
authors.affiliation: Division of Public Health Sciences, Department of Surgery, Washington University in St. Louis School of Medicine, St. Louis, MO, USA.
authors.forename: Melody S
authors.initials: MS
authors.lastname: Goodman
authors.forename: Yi
authors.initials: Y
authors.lastname: Li
keywords: Conditional logistic regression; Kernel smoother; Model diagnostics