MEGH: A parametric class of general hazard models for clustered survival data.

ABSTRACT: In many applications of survival data analysis, the individuals are treated in different medical centres or belong to different clusters defined by geographical or administrative regions. The analysis of such data requires accounting for between-cluster variability. Ignoring such variability would impose unrealistic assumptions in the analysis and could affect the inference on the statistical models. We develop a novel parametric mixed-effects general hazard (MEGH) model that is particularly suitable for the analysis of clustered survival data. The proposed structure generalises the mixed-effects proportional hazards and mixed-effects accelerated failure time structures, among other structures, which are obtained as special cases of the MEGH structure. We develop a likelihood-based algorit

SUBMITTER: Rubio FJ 

PROVIDER: S-EPMC9315191 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature