Premium
Checking hazard regression models using pseudo‐observations
Author(s) -
Perme Maja Pohar,
Andersen Per Kragh
Publication year - 2008
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.3401
Subject(s) - censoring (clinical trials) , covariate , computer science , goodness of fit , complement (music) , proportional hazards model , statistics , regression analysis , econometrics , mathematics , machine learning , gene , biochemistry , chemistry , complementation , phenotype
Graphical methods for model diagnostics are an essential part of the model fitting procedure. However, in survival analysis, the plotting is always hampered by the presence of censoring. Although model specific solutions do exist and are commonly used, we present a more general approach that covers all the models using the same framework. The pseudo‐observations enable us to calculate residuals for each individual at each time point regardless of censoring and provide methods for simultaneously checking all the assumptions of both the Cox and the additive model. We introduce methods for single as well as multiple covariate cases and complement them with corresponding goodness‐of‐fit tests. The methods are illustrated on simulated as well as real data examples. Copyright © 2008 John Wiley & Sons, Ltd.