Checking hazard regression models using pseudo-observations.

Statistics in Medicine
Maja Pohar Perme, Per Kragh Andersen

Abstract

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.

References

Aug 1, 1989·Statistics in Medicine·O O Aalen
Mar 10, 2007·Statistics in Medicine·John P KleinPer Kragh Andersen
Jan 18, 2008·Computer Methods and Programs in Biomedicine·John P KleinMaja Pohar Perme

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Citations

Sep 27, 2012·Lifetime Data Analysis·Bernhard HallerKurt Ulm
Jan 15, 2014·Lifetime Data Analysis·Stefan Nygaard HansenErik Thorlund Parner
Dec 4, 2012·Biometrical Journal. Biometrische Zeitschrift·Aris Perperoglou
Jul 11, 2013·Statistics in Medicine·P K Andersen
Mar 31, 2015·Cancer Epidemiology·Séverine Gilard-PiocCatherine Quantin
Nov 26, 2014·Lifetime Data Analysis·Jianing LiMei-Jie Zhang
Aug 12, 2014·BMC Medical Research Methodology·Federico AmbrogiPatrizia Boracchi
Aug 6, 2009·Statistical Methods in Medical Research·Per Kragh Andersen, Maja Pohar Perme
Aug 3, 2013·Statistical Methods in Medical Research·Seungbong HanKam-Wah Tsui
Mar 1, 2018·Lifetime Data Analysis·Klemen PavličPer Kragh Andersen
May 8, 2021·BMC Medical Research Methodology·François Lefebvre, Roch Giorgi

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