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.
ClinicalTrials, Econometrics, SocialSciences, Survival
Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".
For attribution, please cite this work as
Gu, et al., "The R Journal: Stratified Weibull Regression Model for Interval-Censored Data", The R Journal, 2014
BibTeX citation
@article{RJ-2014-003,
author = {Gu, Xiangdong and Shapiro, David and Hughes, Michael D. and Balasubramanian, Raji},
title = {The R Journal: Stratified Weibull Regression Model for Interval-Censored Data},
journal = {The R Journal},
year = {2014},
note = {https://doi.org/10.32614/RJ-2014-003},
doi = {10.32614/RJ-2014-003},
volume = {6},
issue = {1},
issn = {2073-4859},
pages = {31-40}
}