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AOM Symposium: How to Improve on Statistical Significance: Effect Sizes, CIs, Graphs and Baseline Models

  • 1.  AOM Symposium: How to Improve on Statistical Significance: Effect Sizes, CIs, Graphs and Baseline Models

    Posted 06-20-2015 06:15

    Symposium at Academy of Management Conference

    Sponsors: RM, OMT, ENT


    How to Improve on Statistical Significance: Effect Sizes, CIs, Graphs and Baseline Models

    William H. Starbuck, University of Oregon
    Andreas Schwab, Iowa State University

    Eric Abrahamson, Columbia University

    Samuel Holloway, University of Portland


    Tuesday, Aug 11 2015 at 3:00PM - 4:30PM

    The Fairmont Hotel Vancouver in Gabriola Island

    Academy of Management Conference in Vancouver, Canada


    This symposium will introduce and discuss how scholars can improve upon the Null Hypothesis Significance Tests (NHSTs), which are currently constraining the production of knowledge in management science.  The extensive use of NHST in quantitative research has led to the accumulation of "statistically significant" results that are both too small to be practically relevant and so small that they are unlikely to replicate.  In a field that aspires to provide useful advice to managers, we need to focus on practically important effects that are robust across a wide variety of settings.  The proposed symposium introduces and discusses alternative approaches to address NHST limitations -- such as, effect size measures, confidence intervals, graphs, meta analyses and baseline modeling.  A final "Question and Answer" session will offer additional opportunities for specific discussions, advice and recommendations.


    For further information on this session, please contact Andreas Schwab (aschwab@iastate.edu).

     

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