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AOM Members can access two CARMA lectures this Friday

  • 1.  AOM Members can access two CARMA lectures this Friday

    Posted 02-13-2024 22:35

    AOM Members-

    Are you interested in learning more about questionnaire measures or machine learning? Join CARMA for our upcoming Webcast Lecture Series on Friday, February 16, as we cover these two topics. CARMA is a non-profit academic center at Texas Tech University now in our 26th year of providing research methods education. We are pleased to offer live online access to our Webcast Lectures free of charge to AOM Student and Academic Members as part of the new 2024 AOM-CARMA Affiliate Program.

    ·      Questionnaire Measures as IVs

    Dr. John Antonakis, University of Laussane

    Friday, February 16 | 9:00 AM EST (New York)/1:00 PM GMT (London)


    In leadership, or other areas of management and applied psychology, researchers often obtain ratings behaviors of target individuals using questionnaires. I will show why variation in questionnaire ratings of leadership ("x")-or of any other unit of study for that matter-should not be used as a gauge of variation of actual behavior. What x measures is not just leader behavior but much more. It is an evaluative judgment, which is influenced by many omitted causes at the target, the ratee, and the context in which the rating occurs. For example, suppose we wish to measure leader charisma using questionnaires. At the target level, it is possible that smarter, more extraverted, and more attractive individuals (let's call these variables S) rated as having more charisma. At the rater level, mood, rater personality, or other idiosyncratic factors (let's call these variables Z) may influence how the target is rated. Raters can also be biased by performance signals; their knowledge of how effective the leader is or how well the organization is going (let's call the P) may bias how charismatic they see the target to be. The problem is this: Are S, Z, and P measured and put alongside x in the regression model? What if S, Z, and P also cause y? If these omitted variables are not measured and included in the model, then we may find a significant correlation between x and y; however, this correlation may be driven by S, Z, or P. Failure to account for omitted causes misleads theory and practice. It may be that x causes nothing and that it is S, Z, or P that are driving both x and y. We will discuss the implications of this problem and how it affects other areas of research in management and applied psychology.

    ·      Machine Learning in the Organizational Sciences: From There to Here and What's Next

    Dr. Andrew Speer, Indiana University

    Friday, February 16 | 12:00 PM EST (New York)/4:00 PM GMT (London)


    In this webcast, I will introduce core machine learning (ML) concepts and how they are applied within the organization sciences. I will then discuss how modern prediction methods were used within the organizational sciences, where they are likely to be most advantageous, challenges experienced when applying ML to organizational data, and how newer advancements in artificial intelligence are changing the way we make use of data within organizations.

    To access CARMA's live online Webcast Lectures, follow these steps:

    • Sign into your AOM account.
    • Click on your name at the top of the screen.
    • In the information area, click the CARMA globe logo.
    • When prompted, click "Access CARMA" button.
    • This button will take you to CARMA's Affiliate Program Access page.
    • On the access page click the "CARMA User Area" button.
    • From within the CARMA User Area, click the "Access Live Events" tab to join our upcoming events.

    I hope you can join us for these great lectures. If you have trouble accessing your AOM-CARMA Affiliate Program User Account, email us at carma@ttu.edu.

    Dr. Larry Williams, CARMA Director


    Larry Williams
    Texas Tech University
    Lincoln NE
    (806) 834-1479