Title
Designs and Polydesigns for Partially Controlled Studies
Speaker
Fan Li, Johns Hopkins University
Abstract
In an increasingly common class of studies, the goal is to evaluate causal effects of treatments that are only partially controlled by the investigator. In such studies there are two conflicting features: (1) a model on the full cohort design and data can identify the causal effects of interest, but can be sensitive to extreme regions of that design's data, where model specification can have more impact; and (2) models on a reduced design (i.e., a subset of the full data), for example, conditional likelihood on matched subsets of data, can avoid such sensitivity, but do not generally identify the causal effects. We propose a general framework, ``polydesign'', that can both identify causal effects and also is robust to model specification by exploring combinations of both the full and reduced designs. We discuss implementation of polydesign methods, and provide an illustration in the evaluation of a Needle Exchange Program. We further discuss strategies of designing location-cotrolled follow-up studies, in order to achieve larger treatment benefit and to increase the accurary of evaluation. This is a joint work with Constantine Frangakis.
Meet the speaker in Room 212 Cockins Hall at 4:30 p.m. Refreshments will be served.
