A Multi-parameter regression model for interval censored survival data

01/28/2019
by   Defen Peng, et al.
0

We develop flexible multi-parameter regression survival models for interval censored survival data arising in longitudinal prospective studies and longitudinal randomised controlled clinical trials. A multi-parameter Weibull regression survival model, which is wholly parametric, and has non-proportional hazards, is the main focus of the paper. 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 re-analysis of data from the Signal Tandmobiel^ study. The results demonstrate that the multi-parameter regression model with frailty is computationally efficient and provides an excellent fit to the data.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
05/05/2020

Semiparametric analysis of clustered interval-censored survival data using Soft Bayesian Additive Regression Trees (SBART)

Popular parametric and semiparametric hazards regression models for clus...
research
01/14/2019

An Ensemble Method for Interval-Censored Time-to-Event Data

Interval-censored data analysis is important in biomedical statistics fo...
research
06/14/2022

Neural interval-censored Cox regression with feature selection

The classical Cox model emerged in 1972 promoting breakthroughs in how p...
research
01/10/2019

Multi-Parameter Regression Survival Modelling: An Alternative to Proportional Hazards

It is standard practice for covariates to enter a parametric model throu...
research
06/10/2022

A simulation study of the estimation quality in the double-Cox model with shared frailty for non-proportional hazards survival analysis

The Cox regression, a semi-parametric method of survival analysis, is ex...
research
06/26/2021

Parmsurv: a SAS Macro for Flexible Parametric Survival Analysis with Long-Term Predictions

Health economic evaluations often require predictions of survival rates ...
research
06/30/2022

Designing to detect heteroscedasticity in a regression model

We consider the problem of designing experiments to detect the presence ...

Please sign up or login with your details

Forgot password? Click here to reset