Journal of Computational and Graphical Statistics (2002), 11(4), 784-798.
T. Cai1, R.J. Hyndman2 and M.P. Wand3
- Department of Biostatistics, University of Washington, Seattle, Washington 98195, USA.
- Department of Econometrics and Business Statistics, Monash University, VIC 3800, Australia.
- Department of Biostatistics, Harvard University, Boston, Massachusetts 02115, USA.
Abstract: We propose a new method for estimation of the hazard function from a set of censored failure time data, with a view to extending the general approach to more complicated models. The approach is based on a mixed model representation of penalized spline hazard estimators. One payoff is the automation of the smoothing parameter choice through restricted maximum likelihood. Another is the option to use standard mixed model software for automatic hazard estimation.
Keywords: non-parametric regression; Restricted maximum likelihood; Variance component; Survival analysis.