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A Goodness-of-Fit Test for Multinomial Logistic Regression
Jelle J. Goeman and Saskia le Cessie
Vol. 62, No. 4 (Dec., 2006), pp. 980-985
Published by: International Biometric Society
Stable URL: http://www.jstor.org/stable/4124518
Page Count: 6
You can always find the topics here!Topics: Logistic regression, Regression analysis, P values, Statistical models, Data smoothing, Biometrics, Health outcomes, Null hypothesis, Statistical variance, Approximation
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This article presents a score test to check the fit of a logistic regression model with two or more outcome categories. The null hypothesis that the model fits well is tested against the alternative that residuals of samples close to each other in covariate space tend to deviate from the model in the same direction. We propose a test statistic that is a sum of squared smoothed residuals, and show that it can be interpreted as a score test in a random effects model. By specifying the distance metric in covariate space, users can choose the alternative against which the test is directed, making it either an omnibus goodness-of-fit test or a test for lack of fit of specific model variables or outcome categories.
Biometrics © 2006 International Biometric Society