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Flexible multistate models for interval‐censored data: Specification, estimation, and an application to ageing research
Author(s) -
Machado Robson J. M.,
Hout Ardo
Publication year - 2018
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.7604
Subject(s) - parametric statistics , semiparametric model , semiparametric regression , computer science , estimation , hazard , interval (graph theory) , proportional hazards model , maximum likelihood , parametric model , statistics , confidence interval , econometrics , hazard ratio , mathematics , engineering , chemistry , systems engineering , organic chemistry , combinatorics
Continuous‐time multistate survival models can be used to describe health‐related processes over time. In the presence of interval‐censored times for transitions between the living states, the likelihood is constructed using transition probabilities. Models can be specified using parametric or semiparametric shapes for the hazards. Semiparametric hazards can be fitted using P ‐splines and penalised maximum likelihood estimation. This paper presents a method to estimate flexible multistate models that allow for parametric and semiparametric hazard specifications. The estimation is based on a scoring algorithm. The method is illustrated with data from the English Longitudinal Study of Ageing.