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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 07-31-2015 22:57

    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).

     



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

    Posted 07-26-2016 11:45

    Symposium

    Program Session: 1767 | Submission: 16282 | Sponsor(s): RM, OMT, OB

    Tuesday, Aug 9 2016 9:45AM - 11:15AM at Anaheim Convention Center in 303C

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

    Beyond Statistical Significance

     

    Organizer & Presenter: William H. Starbuck, U. of Oregon

    Organizer & Presenter: Andreas Schwab, Iowa State U.

    Presenter:                          Eric Abrahamson, Columbia U.

    Presenter:                          Samuel Holloway, U. of Portland

     

    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.

     

    Search Terms: Statistical Significance | Effect Size | Practical Significance

     

     

    Andreas

    Andreas Schwab

    Management Department
    3315 Gerdin Business Building
    Ames, IA 50011-2027
    Phone: +1-515-294 -8119
    Skype: andreas.schwab9

    Email: aschwab@iastate.edu

     

    Academic Profile:  http://www.business.iastate.edu/faculty/?faculty=aschwab

    Research Gate:      https://www.researchgate.net/profile/Andreas_Schwab2/publications

    Google Scholar:     http://scholar.google.com/citations?user=mJbkmOMAAAAJ

    Personal Page:       https://sites.google.com/site/schwabphd/