Monthly Biostatistics Seminar with Pablo Martinez-Camblor, Ph.D., Visiting Assistant Professor, The Dartmouth Institute for Health Policy & Clinical Practice

Jan
15
12:00pm - 1:00pm
Borwell 658W, DHMC
When: 
Monday, January 15, 2018 - 12:00pm to 1:00pm
Where: 

Borwell 658W, DHMC

Pablo Martinez-Camblor, Ph.D., Visiting Assistant Professor,
The Dartmouth Institute for Health Policy & Clinical Practice,
will deliver a talk for our monthly Biostatistics Seminar on
Monday, January 15 at 12:00 p.m. (Borwell 658W, DHMC).

Talk title: "Adjusting for bias introduced by instrumental variable
estimation in the Cox proportional hazards model"

Date: Monday, January 15

Time: 12:00 p.m.

Location: Borwell 658W, DHMC

Summary
Instrumental variable (IV) methods are widely used for estimating average treatment effects in the presence of unmeasured confounders. However, the capability of existing IV procedures, and most notably the two-stage residual inclusion (2SRI) algorithm recommended for use in non-linear contexts, to account for unmeasured confounders in the Cox proportional hazard model is unclear. We show that instrumenting an endogenous treatment induces an unmeasured covariate, referred to as an individual frailty in survival analysis parlance, which, if not accounted for, leads to bias. We propose a new procedure that augments 2SRI with an individual frailty and prove that it is consistent under certain conditions. The finite sample-size behavior is studied across a broad set of conditions via Monte Carlo simulations. Finally, the proposed methodology is used to estimate the average effect of carotid endarterectomy versus carotid stenting on the mortality of patients suffering from carotid artery disease. Results suggest that the 2SRI-frailty estimator generally reduces the bias of both point and interval estimators compared to traditional 2SRI.

Speaker Bio
Dr. Pablo Martinez-Camblor is a Visiting Assistant Professor at The Dartmouth Institute of Health Policy and Clinical Practice. He received a doctoral degree in Statistics from the University of Oviedo (north of Spain). He has worked on different topics including kernel density estimators, k-sample problems, and survival analysis. Currently, he focusses on diagnostic/prognosis problems and on instrumental variables procedures on Cox regression models. His works have been published in prestigious journals including Statistical Methods in Medical Research, Biostatistics, New England Journal of Medicine and Lancet, with more than 150 papers published in peer review journals. In addition, he acts as reviewer in a number of methodological and medical journals including The Lancet.