Open AccessDiagnostic measures for the Cox regression model with missing covariates
Author(s) -
Hongtu Zhu,
Joseph G. Ibrahim,
Ming Hui Chen
Publication year - 2015
Publication title -
biometrika
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.307
H-Index - 122
eISSN - 1464-3510
pISSN - 0006-3444
DOI - 10.1093/biomet/asv047
Subject(s) - covariate , mathematics , statistics , missing data , proportional hazards model , regression analysis , econometrics , regression
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.