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10.1093/biomet/asv047 http://scihub22266oqcxt.onion/10.1093/biomet/asv047 C4760115!4760115!26903666     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Biometrika 2015 ; 102 (4): 907-23 Nephropedia Template TP {{tp|p=26903666|t=2015. Diagnostic measures for the Cox regression model with missing covariates |pdf=|usr=}}{{26903666}} gab.com Text Diagnostic measures for the Cox regression model with missing covariates JO: Biometrika http://www.kidney.de/pget.php?&tw=1&pmid=26903666 #FOAvip We investigate diagnostic measures for assessing the influence of observations and model misspecification on the Cox regression model when there are missing covariate data. Our diagnostics include case-deletion measures, conditional martingale residuals, and score residuals. The Q-distance is introduced to examine the effects of deleting individual observations on the estimates of finite- and infinite-dimensional parameters. Conditional martingale residuals are used to construct goodness-of-fit statistics for testing misspecification of the model assumptions. A resampling method is developed to approximate the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$p$\end{document}-values of the goodness-of-fit statistics. We conduct simulation studies to evaluate our methods, and analyse a real dataset to illustrate their use. Twit Text FOAVip Diagnostic measures for the Cox regression model with missing covariates ????Biometrika http://www.kidney.de/pget.php?&tw=1&pmid=26903666 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26903666 #FOAvip English Wikipedia <ref>{{Cite pmid|26903666}}</ref> Diagnostic measures for the Cox regression model with missing covariates #MMPMID26903666 Zhu H; Ibrahim JG; Chen MH Biometrika 2015[Dec]; 102 (4): 907-23 PMID26903666show ga We investigate diagnostic measures for assessing the influence of observations and model misspecification on the Cox regression model when there are missing covariate data. Our diagnostics include case-deletion measures, conditional martingale residuals, and score residuals. The Q-distance is introduced to examine the effects of deleting individual observations on the estimates of finite- and infinite-dimensional parameters. Conditional martingale residuals are used to construct goodness-of-fit statistics for testing misspecification of the model assumptions. A resampling method is developed to approximate the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$p$\end{document}-values of the goodness-of-fit statistics. We conduct simulation studies to evaluate our methods, and analyse a real dataset to illustrate their use. äDiagnostic measures for the Cox regression model with missing covariat(epmc).pdf DeepDyve Pubget Overpricing