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Quantile-Quantile Plot for Deviance Residuals in the Generalized Linear Model
Marta García Ben and Víctor J. Yohai
Journal of Computational and Graphical Statistics
Vol. 13, No. 1 (Mar., 2004), pp. 36-47
Published by: Taylor & Francis, Ltd. on behalf of the American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of America
Stable URL: http://www.jstor.org/stable/1391143
Page Count: 12
You can always find the topics here!Topics: Regression analysis, Generalized linear model, Statistical models, Logistic regression, Binomials, Linear regression, Statistics, Logistics, Sample size, Diagnostic tools
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The normal quantile-quantile (Q-Q) plot of residuals is a popular diagnostic tool for ordinary linear regression with normal errors. However, for some generalized linear regression models, the distribution of deviance residuals may be very far from normality, and therefore the corresponding normal Q-Q plots may be misleading to check model adequacy. We introduce an estimate of the distribution of the deviance residuals of generalized linear models. We propose a new Q-Q plot where the observed deviance residuals are plotted against the quantiles of the estimated distribution. The method is illustrated by the analysis of real and simulated data.
Journal of Computational and Graphical Statistics © 2004 American Statistical Association