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A local likelihood proportional hazards model for interval censored data
Author(s) -
Betensky Rebecca A.,
Lindsey Jane C.,
Ryan Louise M.,
Wand M. P.
Publication year - 2001
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.993
Subject(s) - covariate , proportional hazards model , statistics , hazard ratio , confidence interval , mathematics , hazard , interval (graph theory) , likelihood function , econometrics , maximum likelihood , chemistry , organic chemistry , combinatorics
We discuss the use of local likelihood methods to fit proportional hazards regression models to right and interval censored data. The assumed model allows for an arbitrary, smoothed baseline hazard on which a vector of covariates operates in a proportional manner, and thus produces an interpretable baseline hazard function along with estimates of global covariate effects. For estimation, we extend the modified EM algorithm suggested by Betensky, Lindsey, Ryan and Wand. We illustrate the method with data on times to deterioration of breast cosmeses and HIV‐1 infection rates among haemophiliacs. Copyright © 2002 John Wiley & Sons, Ltd.