Regression analysis of interval censored competing risk data using a pseudo-value approach

摘要: Interval censored data often occur in an observational study where the subject is followed periodically. Instead of observing exact failure time, two inspection times that include it are available. There several methods to analyze interval time (Sun, 2006). However, presence competing risks, few have been suggested estimate covariate effect on risk data. A subdistribution hazard model a commonly used regression because has one-to-one correspondence with cumulative incidence function. Alternatively, Klein and Andersen (2005) proposed pseudo-value approach directly uses In this paper, we consider extension into coefficients. The pseudo-values generated from estimated function then become response variables generalized estimating equation. Simulation studies show method performs well situations HIV-AIDS cohort analyzed as real example.