Semiparametric multi-parameter regression survival modelling

Research output: Contribution to journalJournal articleResearchpeer-review

Kevin Burke, Frank Eriksson, C. B. Pipper

We consider a log-linear model for survival data, where both the location and scale parameters depend on covariates and the baseline hazard function is completely unspecified. This model provides the flexibility needed to capture many interesting features of survival data at a relatively low cost in model complexity. Estimation procedures are developed and asymptotic properties of the resulting estimators are derived using empirical process theory. Finally, a resampling procedure is developed to estimate the limiting variances of the estimators. The finite sample properties of the estimators are investigated by way of a simulation study, and a practical application to lung cancer data is illustrated.
Original languageEnglish
JournalScandinavian Journal of Statistics
Number of pages37
ISSN0303-6898
Publication statusPublished - 2019

    Research areas

  • stat.ME, 62N01, 62N02, 62N03

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