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Department seminar by Mireille Schnitzer, McGill UniversityExport this event to calendar

Wednesday, December 19, 2012 — 2:00 PM EST

Targeted maximum likelihood estimation of the impact of hepatitis C (HCV) clearance on time to end-stage liver disease in a population co-infected with HIV

In complex longitudinal and survival settings where confounding of the effect of interest occurs through time-dependent variables, special statistical techniques are required to refine a "causal" quantity of interest. In particular, estimation of marginal parameters and contrasts between such parameters can produce statistical inference with intuitive interpretations.

In this talk, I describe a case study analysis of the Canadian Co-Infection Cohort (CCC), which follows participants who have been diagnosed with both HIV and Hepatitis C (HCV). Our survival analysis estimates the causal effect of the clearance of HCV on the onset of end-stage liver disease.
 
The primary method used in our analysis was Targeted Maximum Likelihood Estimation (TMLE) which we extended and implemented for the survival setting. I will describe some of the theory, and modeling details and benefits of the TMLE framework as well as the challenges involved in implementation for the CCC analysis.
Location 
M3 - Mathematics 3
3127
200 University Avenue West

Waterloo, ON N2L 3G1
Canada

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