Date: 2013-01-11

Time: 14:30-15:30

Location: BURN 1205

Abstract:

Statisticians are often faced with budget concerns when conducting studies. The collection of some covariates, such as genetic data, is very expensive. Other covariates, such as detailed histories, might be difficult or time-consuming to measure. This helped bring about the invention of the nested case-control study, and its more generalized version, risk-set sampled survival analysis. The literature has a good discussion of the properties of risk-set sampling in standard right-censored survival data. My interest is in extending the methods of risk-set sampling to left-truncated survival data, which arise in prevalent longitudinal studies. Since prevalent studies are easier and cheaper to conduct than incident studies, this extension is extremely practical and relevant. I will introduce the partial likelihood in this scenario, and briefly discuss the asymptotic properties of my estimator. I will also introduce Bayesian methods for standard survival analysis, and discuss methods for analyzing risk-set-sampled survival data using Bayesian methods.

Speaker

Ana Best is a PhD candidate in our department. She works with David Wolfson.