Stratifiedweibull regression model for interval-censored data

3Citations
Citations of this article
896Readers
Mendeley users who have this article in their library.

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.

Cite

CITATION STYLE

APA

Gu, X., Shapiro, D., Hughes, M. D., & Balasubramanian, R. (2014). Stratifiedweibull regression model for interval-censored data. R Journal, 6(1), 31–40. https://doi.org/10.32614/rj-2014-003

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free