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Quantitative Issues in Cancer Research Working Seminar
February 6 @ 1:00 pm - 1:50 pm
Doctoral Student, Department of Biostatistics, Harvard University
Semi-Competing Risks for the Case-Cohort Study Design
Abstract: The advent of large observational databases and cohort studies introduces a rich source of data. Often, specific risk factors of interest to researchers may either not have been collected in resource-limited settings or are difficult to ascertain due to cost constraints. The case-cohort study design is well-known as a cost-effective outcome-dependent sampling scheme for studies embedded within large cohort studies. However, when interest lies in semi-competing risks, a setting where a non-terminal event and a terminal event (usually death) are investigated simultaneously, there are currently no statistical methods for the analysis of data arising from a case-cohort design. We propose a model for estimation and inference for this study design and provide initial simulation data for this framework.