Open Access
July, 1981 Logistic Regression Diagnostics
Daryl Pregibon
Ann. Statist. 9(4): 705-724 (July, 1981). DOI: 10.1214/aos/1176345513


A maximum likelihood fit of a logistic regression model (and other similar models) is extremely sensitive to outlying responses and extreme points in the design space. We develop diagnostic measures to aid the analyst in detecting such observations and in quantifying their effect on various aspects of the maximum likelihood fit. The elements of the fitting process which constitute the usual output (parameter estimates, standard errors, residuals, etc.) will be used for this purpose. With a properly designed computing package for fitting the usual maximum-likelihood model, the diagnostics are essentially "free for the asking." In particular, good data analysis for logistic regression models need not be expensive or time-consuming.


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Daryl Pregibon. "Logistic Regression Diagnostics." Ann. Statist. 9 (4) 705 - 724, July, 1981.


Published: July, 1981
First available in Project Euclid: 12 April 2007

zbMATH: 0478.62053
MathSciNet: MR619277
Digital Object Identifier: 10.1214/aos/1176345513

Primary: 62F99
Secondary: 62J05 , 62P10

Keywords: generalized linear models , influence curves , iteratively reweighted least squares , leverage points , logistic regression , regression diagnostics , residual analysis

Rights: Copyright © 1981 Institute of Mathematical Statistics

Vol.9 • No. 4 • July, 1981
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