Methods for fitting survival regression models with a penalized smoothed hazard function have been recently discussed, even though they could be cumbersome. A simpler alternative which does not require specific software packages could be fitting a penalized piecewise exponential model. In this work the implementation of such strategy in Win- BUGS is illustrated, and preliminary results are reported concerning the application of Bayesian P-splines techniques. The technique is applied to a pre-specified model in which the number and positions of knots were fixed on the basis of clinical knowledge, thus defining a non-standard smoothing problem.
CITATION STYLE
Marano, G., Boracchi, P., & Biganzoli, E. M. (2015). Estimation of a piecewise exponential model by Bayesian P-splines techniques for prognostic assessment and prediction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8623, pp. 183–198). Springer Verlag. https://doi.org/10.1007/978-3-319-24462-4_16
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