Abstract:
:In this paper we give an informal introduction to a robust method for survival analysis which is based on a modification of the usual partial likelihood estimator (PLE). Large sample results lead us to expect reduced bias for this robust estimator compared with the PLE whenever there are even slight violations of the model. In this paper we investigate three types of violation: (a) varying dependency structure of survival time and covariates over the sample; (b) omission of influential covariates, and (c) errors in the covariates. The simulations presented support the above expectation. Analyses of data sets from cancer epidemiology and from a clinical trial in lung cancer illustrate that a better fit and additional insights may be gained using robust estimators.
journal_name
Stat Medjournal_title
Statistics in medicineauthors
Minder CE,Bednarski Tdoi
10.1002/(SICI)1097-0258(19960530)15:10<1033::AID-Ssubject
Has Abstractpub_date
1996-05-30 00:00:00pages
1033-47issue
10eissn
0277-6715issn
1097-0258pii
10.1002/(SICI)1097-0258(19960530)15:10<1033::AID-Sjournal_volume
15pub_type
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