"Everything should be made as simple as possible, but not simpler." - Albert Einstein

Seminar Announcement

Analysis of Censored Survival Times with Missing Covariates
Using the EM Algorithm

Josh Horstman, M.S. Candidate, Department of Statistics, Colorado State University.

Monday, November 3, 2008

9:30 a.m. 223 Weber


We consider the use of the EM algorithm for maximum likelihood estimation in
the analysis of censored survival times, both with and without missing covariate values.
After attempts to complete the EM algorithm analytically fail, the EM gradient method
of Lange (1995) is invoked to complete the M step. Variance estimation follows using
the SEM algorithm of Meng and Rubin (1991). In the case of missing covariates, we
employ the Monte Carlo EM algorithm as used by Ibrahim, Chen, and Lipsitz (1999)
with a simple bootstrap method for variance estimation. Monte Carlo simulation is
based upon a Gibbs sampler using several sampling mechanisms including rejection


Advisory Committee:

Geof Givens, Adviser

Dan Cooley, Committee Member

David Thompson (Department of Atmospheric Science)