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2015年4月10日(金)16:20~17:50 IPP研究会

報告者	:原田 勝孝 氏 ( 政策研究大学院大学 助教授 )
テーマ :Sensitivity Analysis for Unmeasured Confounding:
        Extension to Heterogeneous Treatments and Beyond

日 時	:2015年4月10日(金) 16:20-17:50
場 所	:大阪大学 大学院 国際公共政策研究科棟 6階 会議室
言 語   :英語
主 催	:IPP研究会
お問い合わせ:松繁研究室 山本 studio-pine*osipp.osaka-u.ac.jp (*には@をお入れください。)
【概 要】
  A major obstacle to developing evidenced-based policy is the difficulty in implementing randomized experiments to answer all causal questions of interest. When using a non-experimental study, it is critical to assess how much the results could be affected by unmeasured confounding. We present a set of graphical and numeric tools to explore the sensitivity of causal estimates to the presence of an unmeasured confounder. We characterize the confounder through two parameters that describe the relationships between 1) the confounder and the treatment assignment and 2) the confounder and the outcome variable. Our approach has two primary advantages over similar approaches that are currently implemented in standard software. First, it can be applied to both continuous and binary treatment variables. Second, our method for binary treatment variables allows the researcher to specify three possible estimands (average treatment effect, effect of the treatment on the treated, effect of the treatment on the controls). We demonstrate the efficacy of the method through simulations. We illustrate its potential usefulness in practice using LaLonde's (1986) constructed observational data. When time allows, we also introduce a new extension of our algorithm to nonlinear response surface using Bayesian Additive Regression Trees (BART) technique.  

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