arXiv Open Access 2023

Smooth hazards with multiple time scales

Angela Carollo Paul H. C. Eilers Hein Putter Jutta Gampe

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Abstrak

Hazard models are the most commonly used tool to analyse time-to-event data. If more than one time scale is relevant for the event under study, models are required that can incorporate the dependence of a hazard along two (or more) time scales. Such models should be flexible to capture the joint influence of several times scales and nonparametric smoothing techniques are obvious candidates. P-splines offer a flexible way to specify such hazard surfaces, and estimation is achieved by maximizing a penalized Poisson likelihood. Standard observations schemes, such as right-censoring and left-truncation, can be accommodated in a straightforward manner. The model can be extended to proportional hazards regression with a baseline hazard varying over two scales. Generalized linear array model (GLAM) algorithms allow efficient computations, which are implemented in a companion R-package.

Topik & Kata Kunci

stat.ME stat.AP

Penulis (4)

Angela Carollo

Paul H. C. Eilers

Hein Putter

Jutta Gampe

Format Sitasi

APA MLA BibTeX

Carollo, A., Eilers, P.H.C., Putter, H., Gampe, J. (2023). Smooth hazards with multiple time scales. https://arxiv.org/abs/2305.09342

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Informasi Jurnal

Tahun Terbit: 2023
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓