Model diagnostics for marginal regression analysis of correlated binary data |
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Authors: | Ming Tan Yingsheng Qu Michael HKutner |
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Institution: | Department of Biostatistics and Epidemiology , The Cleveland Clinic Foundation , Cleveland, Ohio, 44195 |
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Abstract: | We propose several diagnostic methods for checking the adequacy of marginal regression models for analyzing correlated binary data. We use a parametric marginal model based on latent variables and derive the projection (hat) matrix, Cook's distance, various residuals and Mahalanobis distance between the observed binary responses and the estimated probabilities for a cluster. Emphasized are several graphical methods including the simulated Q-Q plot, the half-normal probability plot with a simulated envelope, and the partial residual plot. The methods are illustrated with a real life example. |
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Keywords: | model adequacy checking GEE correlated logistic regression |
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