A local likelihood proportional hazards model for interval censored data

Rebecca A. Betensky, Jane C. Lindsey, Louise M. Ryan, M. P. Wand

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)263-275
Number of pages13
JournalStatistics in Medicine
Issue number2
StatePublished - Jan 30 2002


  • Interval censored data
  • Local likelihood methods
  • Proportional hazards
  • Regression model

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability


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