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AOM PDW: What Would it take to Change an Inference? Quantifying the Robustness of Causal Inferences

  • 1.  AOM PDW: What Would it take to Change an Inference? Quantifying the Robustness of Causal Inferences

    Posted 07-26-2023 16:41

    Fellow scholars,

    I'd like to invite you to an exciting and timely AOM PDW, which will teach you a new method about how to quantify the robustness of our causal inferences. Below is a summary and information for the session.


    Hope to see you there!

    Derek

    Summary: Participants in this PDW will learn several approaches for quantifying the robustness of a causal inference. These provide a more precise language for producers and consumers to talk about potential concerns to inferences (e.g., omitted variables). The Impact Threshold for a Confounding Variable (ITCV) will be introduced to show participants how they can quantify how strong the correlations associated with an omitted variable must be to overturn an inference. The Robustness of Inference to Replacement (RIR) will be introduced to show participants how they can quantify what percentage of cases would have to be replaced with cases for which there was no effect of the predictor of interest to change the inference. Participants will learn to use the on-line application, spreadsheet, and the konfound macros in Stata and R. We will discuss guidelines for the application of sensitivity analysis in management research. These approaches allow researchers across a broad range of topic areas to debate the strength of evidence in intuitive and concrete terms.

    Session 136

    Friday August 04, 12:00 PM - 05:00 PM

    303, Hynes

    Session: https://aom.econference.io/public/A5p5d1k/main/sessions/29190



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    Derek Harmon
    University of Michigan
    Ann Arbor MI
    (651) 271-0320
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