YSPH Biostatistics Seminar- “Two problems of estimation in the presence of semi competing or competing risks”

Note: BIS 526 students are required to attend in person. Others are invited to attend in person but may also attend via zoom.

Speaker- Rebecca Betensky, PhD

Title- “Two problems of estimation in the presence of semi competing or competing risks”

Abstract

I will discuss two problems that involve competing risks. The first problem is that of estimation in the presence of semicompeting risks and left truncation. I will present three nonparametric maximum likelihood estimators under different models for censoring. The second problem is that of estimation in the presence of a competing risk with an intermediate event that terminates the risk of a different competing risk. In the absence of censoring, this early termination of risk can be ignored for estimation of the cumulative incidence function (CIF). In the presence of censoring, I will show that in large samples, early termination of risk can be ignored as well for certain CIF estimators. I will discuss the implications of this for regression modeling via the cause specific hazard and via the subdistribution hazard. I demonstrate these results in simulations and an analysis of dementia with recovered COVID, with the competing risk of dementia with Long COVID and intermediate terminating event of onset of Long COVID.