Related Experiment Video
Updated: Jan 16, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Quantile regression model for interval-censored data with competing risks
Amirah Afiqah Binti Che Ramli1, Yang-Jin Kim1
1Department of Statistics, Research Institute of Natural Science, Sookmyung Women's University, Seoul, Korea.
None:
Our interest is to provide the methodology for estimating quantile regression model for interval-censored competing risk data. Lee and Kim [Analysis of interval censored competing risk data via nonparametric multiple imputation. Stat. Biopharm. Res. 13 (2020), pp. 367-374.] applied a censoring complete data concept suggested by Ruan and Gray [Analyses of cumulative incidence function via non-parametric multiple imputation. Sta. Med. 27 (2008), pp. 5709-5724.] to recover a missing information related with competing events. In this paper, we also applied it to a quantile regression model. The simulated censoring times of the competing events are generated with a multiple imputation technique and the survival function of right censoring times. The performance of suggested methods is evaluated by comparing with the result of a simple imputation method under several distributions and sample sizes. The AIDS dataset is analyzed to estimate the effect of several covariates on the quantiles of cause-specific CIF as a real data analysis.
Related Concept Videos
Censoring Survival Data
Comparing the Survival Analysis of Two or More Groups
Hazard Rate
Kaplan-Meier Approach
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time...
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...

