- Decision trees for instantaneous hazard rates with adjustment for covariate effects
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- Abstract:
- We investigate the problem of finding confidence sets for a threshold in the baseline hazard function of the Cox proportional hazards model. The aim is to find an effective way of condensing information in the baseline into a small number of estimable parameters. A binary decision tree is used as a working model, with the jump point (threshold) representing a time at which baseline risk changes abruptly between two levels. We find the asymptotic distribution of estimators of best-fitting parameters under an arbitrary misspecification of the working model. The estimators converge at cube-root rate to a non-normal limit distribution. Two alternate ways of constructing confidence intervals for the threshold are compared. Results from a simulation study and an example concerning a threshold for the age of onset of schizophrenia in a large cohort study are discussed.
- Subject Area:
- Survival Analysis
- Suggested Citation:
Moulinath Banerjee and Ian W. McKeague, "Decision trees for instantaneous hazard rates with adjustment for covariate effects" (June 2006). Columbia University Biostatistics Technical Report Series. Working Paper 5.
http://biostats.bepress.com/columbiabiostat/papers/art5