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Graphics for studying logistic regression models
Authors:Luca Scrucca
Institution:(1) Dipartimento di Scienze Statistiche, Università degli Studi di Perugia, Via Pascoli, 06100 Perugia, Italy
Abstract:In this article we focus on logistic regression models for binary responses. An existing result shows that the log-odds can be modelled depending on the log of the ratio between the conditional densities of the predictors given the response variable. This suggests that relevant statistical information could be extracted investigating the inverse problem. Thus, we present different methods for studying the log-density ratio through graphs, which allow us to select which predictors are needed, and how they should be included in a logistic regression model. We also discuss data analysis examples based on real datasets available in literature in order to provide further insights into the methodology proposed.
Keywords:Logistic regression  binary response  log-density ratio  regression graphics  kernel density estimate  conditional QQ-plot  local likelihood
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