Online Program Home
My Program

Abstract Details

Activity Number: 574 - Recent Advances in Software
Type: Contributed
Date/Time: Wednesday, July 31, 2019 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Computing
Abstract #304121
Title: ICBayes: a Package for Bayesian Semiparametric Regression Analysis of Interval-Censored Data
Author(s): Chun Pan* and Bo Cai and Lianming Wang and Xiaoyan Lin
Companies: Hunter College and University of South Carolina and University of South Carolina and University of South Carolina
Keywords: interval-censored data; Bayesian semiparametric; survival analysis; R package

This presentation introduces the R package ICBayes, which aims to be a comprehensive statistical package for analyzing interval-censored data under different survival regression models. Interval-censored data occur when the time-to-event of interest is not directly observable, but falls within a time interval. The current version of ICBayes incorporates four Bayesian functions for analyzing current status data and general interval-censored data under the proportional hazards model, the proportional odds model, and the probit model. These Bayesian functions all adopt a monotone spline for the unknown non-decreasing baseline function in each semiparametric model and are developed based on model-specific data augmentations. In addition, the package provides the log pseudo marginal likelihood for each method and thus allows users to perform model comparison and selection for a given data set. The use of the package is illustrated through real data examples.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2019 program