Heterogeneous Treatment Effects and Decisionmaking

• Activity Number: 113
• Type: Topic Contributed
• Date/Time: Monday, August 5, 2013 : 8:30 AM to 10:20 AM
• Sponsor: Mental Health Statistics Section
• Author(s): Zhehui Luo*+ and Joseph Gardiner
• Companies: Michigan State University and Michigan State University
• Keywords: Heterogeneity in treatment effects ; comparative effectiveness ; decision making ; major depression

Abstract

Some recent pragmatic trial designs in comparative effectiveness research allow patient treatment choices and thus lead to difficulty in identifying causal effect of specific treatment options across choice sets. We model counterfactual discrete choice behavior and allow unobserved differences between patients in different choice sets and estimate the effect of treatment options across self-selected treatment groups. Following the Manski bounds and Shaikh and Vytlacil bounds we propose a framework to guide treatment decision making based on partially identified models. We explore the extension of the framework from incorporating average treatment effect to heterogeneous treatment effects.