Date: 2018-11-16

Time: 15:30-16:30

Location: BURN 1104

Abstract:

The median residual lifetime function is a statistical quantity which describes the future point in time at which the probability of current survival has dropped by 50%. In deriving an estimator for the median residual lifetime function for length-biased data, the added features of left-truncation and right-censoring must be taken into account.

In this talk, we give a brief description of length-biased failure time data and show that by using a particular non-parametric estimator for the survival function that it is possible to derive the asymptotically most-efficient non-parametric estimator for the median residual lifetime function. We give some details on the proof of the asymptotic results and examine the performance of the estimator using simulated data. We also apply the proposed estimator to the Canadian Study of Health and Aging data set to study the median residual lifetime function of patients with dementia.

This is joint work with Professor Masoud Asgharian.

Speaker

James Hugh McVittie is a PhD student of the Department of Mathematics and Statistics at McGill University.

Organized by the McGill Statistics Group

Seminar website: https://mcgillstat.github.io/