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Endogeneity: An inconvenient truth (a gentle introduction)

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Manage episode 310363386 series 3053367
Content provided by UNIL | Université de Lausanne, John Antonakis, and UNIL. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by UNIL | Université de Lausanne, John Antonakis, and UNIL or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
A key assumption of regression analysis (or structural equation modeling) is that the modeled independent variables are not endogenous. Yet, the problems of endogeneity are not well known to researchers working in many social sciences disciplines (e.g., management, applied psychology, sociology, etc.). When the independent variable has not been exogenously manipulated, there is a strong possibility that its relationship to a dependent variable will not be correctly estimated, leading to spurious findings. This podcast gives a brief and vivid overview to endogeneity and why it is engendered. Prof. John Antonakis discusses the problems of endogeneity using non-technical language and intuitive explanations; he shows that the observed relationship that is estimated can be very misleading when the independent variable is endogenous.
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5 episodes

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Archived series ("Inactive feed" status)

When? This feed was archived on July 17, 2022 23:22 (2y ago). Last successful fetch was on December 04, 2021 11:32 (2+ y ago)

Why? Inactive feed status. Our servers were unable to retrieve a valid podcast feed for a sustained period.

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

Manage episode 310363386 series 3053367
Content provided by UNIL | Université de Lausanne, John Antonakis, and UNIL. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by UNIL | Université de Lausanne, John Antonakis, and UNIL or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
A key assumption of regression analysis (or structural equation modeling) is that the modeled independent variables are not endogenous. Yet, the problems of endogeneity are not well known to researchers working in many social sciences disciplines (e.g., management, applied psychology, sociology, etc.). When the independent variable has not been exogenously manipulated, there is a strong possibility that its relationship to a dependent variable will not be correctly estimated, leading to spurious findings. This podcast gives a brief and vivid overview to endogeneity and why it is engendered. Prof. John Antonakis discusses the problems of endogeneity using non-technical language and intuitive explanations; he shows that the observed relationship that is estimated can be very misleading when the independent variable is endogenous.
  continue reading

5 episodes

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