Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10327707 | Computational Statistics & Data Analysis | 2005 | 18 Pages |
Abstract
Penalized spline (P-spline) smoothing is discussed for hazard regression of multivariable survival data. Non-proportional hazard functions are fitted in a numerically handy manner by employing Poisson regression which results from numerical integration of the cumulative hazard function. Multivariate smoothing parameters are selected by utilizing the connection between P-spline smoothing and generalized linear mixed models. A hybrid routine is suggested which combines the mixed model idea with a classical Akaike information criteria. The model is evaluated with simulations and applied to data on the success and failure of newly founded companies.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Göran Kauermann,