A local likelihood proportional hazards model for interval censored data.
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.
Betensky
Rebecca A
RA
Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, Massachusetts 02115, USA. betensky@hsph.harvard.edu
Lindsey
Jane C
JC
Ryan
Louise M
LM
Wand
M P
MP
D000465:Algorithms; D001943:Breast Neoplasms / Q000188:drug therapy / Q000532:radiotherapy; D005167:Factor VII / Q000008:administration & dosage; D005260:Female; D015658:HIV Infections / Q000209:etiology / Q000635:transmission; D006467:Hemophilia A / Q000821:virology; D006801:Humans; D016013:Likelihood Functions; D009716:Numerical Analysis, Computer-Assisted; D016016:Proportional Hazards Models; D065227:Transfusion Reaction
D005167:Factor VII