Accession Number : ADA135684
Title : Comment on 'Graphical Methods for Assessing Logistic Regression Models,' by Landwehr, Pregibon, and Shoemaker.
Descriptive Note : Techncial rept.,
Corporate Author : CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF STATISTICS
Personal Author(s) : Fienberg,S E ; Gong,G D
PDF Url : ADA135684
Report Date : Sep 1983
Pagination or Media Count : 18
Abstract : The use of graphical methods for diagnostic purposes has an honorable tradition which is rooted in the pioneering work of Anscombe and Tukey and has been developed by Wilk, Gnanadesikan, and a host of others associated with Bell Laboratories. A paper by Landwehr, Pregibon, and Shoemaker (subsequently referred to as LPS) attempts to modify and extend graphical diagnostic displays that have been developed for ordinary regression to be of use for assessing logistic regression models for binary data. They propose displays for each of the three key components of regression diagnostics: goodness of fit, outliner detection, and model specification. Their is a pioneering effort and many useful ideas have emerged from it. Somewhat fuzzy analogies to linear regression are not sufficient to motivate the approaches adopted by LPS. Thus the authors of this paper have attempted to examine critically LPS's diagnostic displays to see if they could determine why in each instance the method works or fails. LPS suggest that the major obstacle in carrying linear regression diagnostics over to the logistic regression setting is the discreteness of binary data. While discreteness may well be a serious problem, additional ones are noted.
Descriptors : *Graphics, *Linear regression analysis, *Mathematical models, Diagnosis(General), Display systems, Logistics, Binary notation, Plotting, Residuals, Probability, Global, Statistical processes, Fitting functions(Mathematics)
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE