Capturing simple and complex time-dependent effects using flexible parametric survival models: A simulation study

Non-proportional hazards are common within time-to-event data and can be modeled using restricted cubic splines in flexible parametric survival models. This simulation study assesses the ability of these models in capturing non-proportional hazards, and the ability of the Akaike Information Criterio...

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Bibliographic Details
Published inCommunications in statistics. Simulation and computation Vol. 50; no. 11; pp. 3777 - 3793
Main Authors Bower, Hannah, Crowther, Michael J., Rutherford, Mark J., Andersson, Therese M.-L., Clements, Mark, Liu, Xing-Rong, Dickman, Paul W., Lambert, Paul C.
Format Journal Article
LanguageEnglish
Published Taylor & Francis 02.11.2021
Subjects
Flexible parametric model
Model selection
Non-proportional hazards
Simulation
Time-dependent effect
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Summary:Non-proportional hazards are common within time-to-event data and can be modeled using restricted cubic splines in flexible parametric survival models. This simulation study assesses the ability of these models in capturing non-proportional hazards, and the ability of the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) in selecting degrees of freedom. The simulation results for scenarios with differing complexities showed little bias in the survival and hazard functions for simple scenarios; bias increased in complex scenarios when fewer degrees of freedom were modeled. Neither AIC nor BIC consistently performed better and both generally selected models with little bias.
ISSN:0361-0918
1532-4141
DOI:10.1080/03610918.2019.1634201