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Pseudo-observations in survival analysis

¹ Department of Biostatistics, University of Copenhagen, O. Farimagsgade 5, PB 2099, DK 1014 Copenhagen K, Denmark
² Department of Biomedical Informatics, University of Ljubljana, Vrazov trg 2, SI-1000 Ljubljana, Slovenia

^* To whom correspondence should be addressed. E-mail: p.k.andersen{at}biostat.ku.dk.

	Abstract

We review recent work on the application of pseudo-observations in survival and event history analysis. This includes regression models for parameters like the survival function in a single point, the restricted mean survival time and transition or state occupation probabilities in multi-state models, e.g. the competing risks cumulative incidence function. Graphical and numerical methods for assessing goodness-of-fit for hazard regression models and for the Fine–Gray model in competing risks studies based on pseudo-observations are also reviewed. Sensitivity to covariate-dependent censoring is studied. The methods are illustrated using a data set from bone marrow transplantation.

First published on August 4, 2009
Statistical Methods in Medical Research 2009, doi:10.1177/0962280209105020


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