# A Multi-parameter regression model for interval censored survival data

## TL;DR

This paper introduces a flexible multi-parameter Weibull regression model for interval censored survival data, applicable in clinical trials and longitudinal studies, accommodating non-proportional hazards and frailty effects.

## Contribution

The paper develops a comprehensive multi-parameter Weibull regression model with extensions for frailty and dispersion, tailored for interval censored survival data, and demonstrates its effectiveness through simulations and real data analysis.

## Key findings

- Model with frailty fits data well
- Computationally efficient estimation method
- Provides flexible modeling of survival data

## Abstract

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$^{\circledR}$ study. The results demonstrate that the multi-parameter regression model with frailty is computationally efficient and provides an excellent fit to the data.