Analysis of interval censored competing risk data with missing causes of failure using pseudo values approach. Issue 4 (4th March 2017)

• Record Type: Journal Article
• Authors: Do, Gipeum; Kim, Yang-Jin
• Is Part Of: Journal of statistical computation and simulation. Volume 87:Issue 4(2017)
• Page Start: 631
• Page End: 639
• Publication Date: 2017-03-04
• Subjects: Competing risk -- cumulative incidence function -- GEE -- interval censored data -- missingcause of failure -- multiple imputation; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5028505
• DOI: 10.1080/00949655.2016.1222530
• Languages: English
• ISSNs: 0094-9655

Abstract

ABSTRACT: Competing risks often occur when subjects may fail from one of several mutually exclusive causes. For example, when a patient suffering a cancer may die from other cause, we are interested in the effect of a certain covariate on the probability of dying of cancer at a certain time. Several approaches have been suggested to analyse competing risk data in the presence of complete information of failure cause. In this paper, our interest is to consider the occurrence of missing causes as well as interval censored failure time. There exist no method to discuss this problem. We applied a Klein–Andersen's pseudo-value approach [Klein, JP Andersen PK. Regression modeling of competing risks data based on pseudovalues of the cumulative incidence function. Biometrics. 2005;61:223–229] based on the estimated cumulative incidence function and a regression coefficient is estimated through a multiple imputation. We evaluate the suggested method by comparing with a complete case analysis in several simulation settings.