I. Willems, J. Beyhum, I. Van Keilegom
In many practical settings, one is interested in studying the time until an event of interest takes place, and therefore, as a first step, collects time-to-event data. A common problem, however, is that the event of interest might not be observed for every subject in the study, leading to incompleteness in the resulting data. This caveat is called censoring, and it greatly complicates the analyses.
Survival analysis is a branch of statistics that is devoted to the study of censored data, and, despite being widely studied, continues to hold many challenges. In this presentation, we start by introducing these challenges and proceed by giving an overview of recent advancements in the field, focusing on contributions by Belgian researchers. In doing so, we explore the intersection of survival analysis with other fields of statistics, including quantile regression, causal inference, and dependence modeling. The last part of the talk focuses on the presenter’s own research.
Keywords: Survival analysis
Scheduled
FENStatS-SEIO: Statistics and Data Science
June 11, 2025 10:30 AM
Auditorio 1. Ricard Vinyes