2019/01/28 by Defen Peng, Peng, Defen, Gilbert MacKenzie +3
Computer Science · Mathematics · #62N01 #62N02 #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Methodology (stat.ME) #Statistical Methods and Bayesian Inference #Statistical Methods and Inference
paper · doi:10.48550/arxiv.1901.09634
openalex publication_date 2019/01/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
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.