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Title: Capturing simple and complex time-dependent effects using flexible parametric survival models: A simulation study
Authors: Bower, H
Crowther, M
Rutherford, M
Andersson, T
Clements, M
Liu, X-R
Paul, D
Lambert, P
First Published: 8-Jul-2019
Publisher: Taylor & Francis
Citation: Communications in Statistics - Simulation and Computation, 2019
Abstract: 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
eISSN: 1532-4141
Links: TBA
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © the authors, 2019. This is an open-access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Description: Supplemental data for this article can be accessed at
Appears in Collections:Published Articles, Dept. of Health Sciences

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