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      How Conditioning on Posttreatment Variables Can Ruin Your Experiment and What to Do about It : STOP CONDITIONING ON POSTTREATMENT VARIABLES IN EXPERIMENTS

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      American Journal of Political Science
      Wiley-Blackwell

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          Marginal Structural Models and Causal Inference in Epidemiology

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            Yes, but what's the mechanism? (don't expect an easy answer).

            Psychologists increasingly recommend experimental analysis of mediation. This is a step in the right direction because mediation analyses based on nonexperimental data are likely to be biased and because experiments, in principle, provide a sound basis for causal inference. But even experiments cannot overcome certain threats to inference that arise chiefly or exclusively in the context of mediation analysis-threats that have received little attention in psychology. The authors describe 3 of these threats and suggest ways to improve the exposition and design of mediation tests. Their conclusion is that inference about mediators is far more difficult than previous research suggests and is best tackled by an experimental research program that is specifically designed to address the challenges of mediation analysis.
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              Separating the Shirkers from the Workers? Making Sure Respondents Pay Attention on Self-Administered Surveys

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                Author and article information

                Journal
                American Journal of Political Science
                American Journal of Political Science
                Wiley-Blackwell
                00925853
                March 30 2018
                :
                :
                Article
                10.1111/ajps.12357
                01748401-c65a-427e-b1c5-cdbb4435f07b
                © 2018

                http://doi.wiley.com/10.1002/tdm_license_1.1

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