Biostatistics Seminar Series

## Estimating the Per Protocol Effect of Aspirin - Ashley I. Naimi, University of Pittsburgh

Thursday 4/11 3:30PM - 4:30PM

Public Health Lecture Hall (A115)

Public Health Lecture Hall (A115)

**G Computation for Estimating the Per Protocol Effect of Aspirin on Pregnancy Outcomes**

While randomized trials are often considered to be the "gold standard" for estimating treatment effects, they are subject to complications when participants do not comply with assigned treatment categories. Non-compliance with study protocol is particularly challenging to deal with in pragmatic trials, when treatment consists of a series of actions over a long period. Standard "as treated" or "per protocol" approaches can be inconsistent due to post-randomization confounding and selection bias. Here, we show how the g computation algorithm (Robins 1986 *Mathematical Modelling*; 7:1393-1512) can be used to estimate per protocol effects in the presence of time-dependent post-randomization confounding using data from a trial of the effect of low dose aspirin on pregnancy outcomes.

Last Updated On Monday, April 8, 2019 by Tang, Lu

Created On Monday, January 7, 2019