The R Journal: article published in 2014, volume 6:1

Stratified Weibull Regression Model for Interval-Censored Data
Xiangdong Gu, David Shapiro, Michael D. Hughes and Raji Balasubramanian , The R Journal (2014) 6:1, pages 31-40.

Abstract Interval censored outcomes arise when a silent event of interest is known to have occurred within a specific time period determined by the times of the last negative and first positive diagnostic tests. There is a rich literature on parametric and non-parametric approaches for the analysis of interval-censored outcomes. A commonly used strategy is to use a proportional hazards (PH) model with the baseline hazard function parameterized. The proportional hazards assumption can be relaxed in stratified models by allowing the baseline hazard function to vary across strata defined by a subset of explanatory variables. In this paper, we describe and implement a new R package straweib, for fitting a stratified Weibull model appropriate for interval censored outcomes. We illustrate the R package straweib by analyzing data from a longitudinal oral health study on the timing of the emergence of permanent teeth in 4430 children.

Received: 2013-07-19; online 2014-03-03
CRAN packages: survival, straweib
CRAN Task Views implied by cited CRAN packages: ClinicalTrials, Econometrics, SocialSciences, Survival

This article is licensed under a Creative Commons Attribution 3.0 Unported license .

@article{RJ-2014-003,
  author = {Xiangdong Gu and David Shapiro and Michael D. Hughes and
          Raji Balasubramanian},
  title = {{Stratified Weibull Regression Model for Interval-Censored
          Data}},
  year = {2014},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2014-003},
  url = {https://doi.org/10.32614/RJ-2014-003},
  pages = {31--40},
  volume = {6},
  number = {1}
}