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Fit Assessment and Identification of Functional Form in Logistic Regression
Author(s) -
Minkin Salomon
Publication year - 1989
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.2307/2348064
Subject(s) - logistic regression , identification (biology) , statistics , mathematics , psychology , computer science , biology , ecology
SUMMARY For the analysis of binary data using logistic regression, there is a need for simple techniques for detecting model inadequacies and suggesting corrective actions. This paper proposes an approach based on the use of line segments to approximate the effect of a predictor. This provides the basis for easily implemented goodness‐of‐fit tests and graphical methods for identifying the nature of the non‐linearities. Methods for selecting the join points are discussed, and their use is illustrated with data from breast cancer patients.