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Diagnostic Measures for the Cox Regression Model with Missing Covariates.

ABSTRACT: This paper investigates diagnostic measures for assessing the influence of observations and model misspecification in the presence of missing covariate data for the Cox regression model. Our diagnostics include case-deletion measures, conditional martingale residuals, and score residuals. The Q-distance is proposed to examine the effects of deleting individual observations on the estimates of finite-dimensional and infinite-dimensional parameters. Conditional martingale residuals are used to construct goodness of fit statistics for testing possible misspecification of the model assumptions. A resampling method is developed to approximate the p-values of the goodness of fit statistics. Simulation studies are conducted to evaluate our methods, and a real data set is analyzed to illustrate their use.

SUBMITTER: Zhu H

PROVIDER: S-EPMC4760115 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Diagnostic Measures for the Cox Regression Model with Missing Covariates.

Zhu Hongtu H Ibrahim Joseph G JG Chen Ming-Hui MH

Biometrika 20151104 4

This paper investigates diagnostic measures for assessing the influence of observations and model misspecification in the presence of missing covariate data for the Cox regression model. Our diagnostics include case-deletion measures, conditional martingale residuals, and score residuals. The Q-distance is proposed to examine the effects of deleting individual observations on the estimates of finite-dimensional and infinite-dimensional parameters. Conditional martingale residuals are used to con ...[more]

PMID: 26903666

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