×

zbMATH — the first resource for mathematics

Graphical methods for assessing logistic regression models. (English) Zbl 0531.65080
Summary: In ordinary linear regression, graphical diagnostic displays can be very useful for detecting and examining anomalous features in the fit of a model to data. For logistic regression models, the discreteness of binary data makes it difficult to interpret such displays. Modifications and extensions of linear model displays lead to three methods for diagnostic checking of logistic regression models. Local mean deviance plots are useful for detecting overall lack of fit. Empirical probability plots help point out isolated departures from the fitted model. Partial residual plots, when smoothed to show underlying structure, help identify specific causes of lack of fit. These methods are illustrated through the analyses of simulated and real data.

MSC:
65C99 Probabilistic methods, stochastic differential equations
65S05 Graphical methods in numerical analysis
65D10 Numerical smoothing, curve fitting
62J05 Linear regression; mixed models
Software:
alr3
PDF BibTeX XML Cite
Full Text: DOI