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A multiparameter regression model for interval‐censored survival data
Author(s) -
Peng Defen,
MacKenzie Gilbert,
Burke Kevin
Publication year - 2020
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.8508
Subject(s) - proportional hazards model , statistics , interval (graph theory) , weibull distribution , computer science , survival analysis , accelerated failure time model , regression , parametric statistics , regression analysis , confidence interval , parametric model , econometrics , mathematics , combinatorics
We develop flexible multiparameter regression (MPR) survival models for interval‐censored survival data arising in longitudinal prospective studies and longitudinal randomised controlled clinical trials. A multiparameter Weibull regression survival model, which is wholly parametric, and has nonproportional hazards, is the main focus of the article. We describe the basic model, develop the interval‐censored likelihood, and extend the model to include gamma frailty and a dispersion model. We evaluate the models by means of a simulation study and a detailed reanalysis of data from the Signal Tandmobiel study. The results demonstrate that the MPR model with frailty is computationally efficient and provides an excellent fit to the data.