Modelling multiple time-scales with flexible parametric survival models.

ABSTRACT:

Background

There are situations when we need to model multiple time-scales in survival analysis. A usual approach in this setting would involve fitting Cox or Poisson models to a time-split dataset. However, this leads to large datasets and can be computationally intensive when model fitting, especially if interest lies in displaying how the estimated hazard rate or survival change along multiple time-scales continuously.

Methods

We propose to use flexible parametric survival models on the log hazard scale as an alternative method when modelling data with multiple time-scales. By choosing one of the time-scales as reference, and rewriting other time-scales as a function of this reference time-scale, users can avoid time-splitting of the data.

Result

Through case-studi

SUBMITTER: Batyrbekova N 

PROVIDER: S-EPMC9644623 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature