Title: Two-phase designs for complex life history processes.
Abstract: Large cohort studies now routinely incorporate biobanks in which biospecimens are stored for future studies aiming to assess their relationship with disease onset or progression. When budget or resources are limited, two-phase designs can be used to guide the sub-sampling of the full cohort in order to create a sub-cohort of individuals whose biomarkers as assayed. The resulting data will feature exposures missing by design for individuals outside of the sub-cohort, and analyses may be based on maximum likelihood, conditional likelihood, or inverse probability weighted estimating functions. This talk will review the general framework for two-phase designs, discuss some recent work involving complex disease processes or observation schemes, and discuss areas warranting further development. Methods are illustrated through application to an arthritis registry and a cancer prevention study. This talk is based on joint work with Fangya Mao and Li Cheung.
Brief introduction: Dr. Richard Cook is a University Professor in the Department of Statistics and Actuarial Science and Faculty of Mathematics Research Chair. He holds a cross-appointment in the School of Public Health (UW). His research interests include the analysis of life history data, the design and analysis of clinical and epidemiological studies, and statistical methods for the analysis of incomplete data. He has published extensively in these areas and written two books with Jerald Lawless (The Statistical Analysis of Recurrent Events, Springer, 2007; Multistate Models for the Analysis of Life History Data, Taylor and Francis, 2018). He is also deeply engaged in collaborative research with other scientists working in transfusion medicine, immunology, and cancer, and he consults widely with industry and government organizations. In 2018, he was awarded the Gold Medal of the Statistical Society of Canada and in 2021 he was named Fellow of the Royal Society of Canada.
Day & Time: Friday, November 3, 2023 at 3:00pm
Location: Odette 108
Counts toward seminar attendance for MSc and PhD students in Math & Stats.