AOM Members-
Want to learn, from the best in our business, about bayesian analysis and causal inference with structural equation models? These topics are covered in two CARMA Webcast Lectures this Friday, January 26 (see abstracts below). And, these live lectures are available to AOM Student and Academic members free of charge as part of the new 2024 AOM-CARMA Affiliate Program. If you want join these events, instructions for how to access via the AOM website is provided at the end of the event information below.
CARMA is a non-profit academic center at Texas Tech University now in our 26th year of providing research methods education. For more information about CARMA, visit our website: https://carmattu.com.
For more information about the 2024 AOM-CARMA Affiliate Program also visit our website:
https://carmattu.com/aomaffiliateinfo/
The lectures described below are also available free of charge to faculty/students from schools that have joined CARMA's 2023-2024 Institutional Member programs (which also include on-demand access to our CARMA Video Library and its 250+ recordings). If this is you, visit our website and use your member login information to join via the CARMA User Area where you will find the zoom link.
If you have questions contact us at carma@tttu.edu. I hope you can join us for these great lectures. Dr. Larry Williams, CARMA Director
Friday January 26
9:00 AM EDT (New York), 2:00 PM BST (London)
Inference with Directed Acyclical Graphs
Dr. Heiko Breitsohl
University of Klagenfurt
Abstract
Causal inference is one of the key challenges in the social, behavioral, and organizational sciences. Researchers invest considerable time and effort into designing their studies to validly model causal effects. Yet, the remaining limitations of their studies often pertain to causal inference, due to the complexities of social and organizational phenomena as well as various constraints faced by researchers. The purpose of this webcast is an introduction to Directed Acyclical Graphs (DAGs), a tool for causal inference that has been making inroads throughout the social sciences. We will walk through what DAGs are (and are not), the basic elements they consist of, their strengths and limitations, and how to apply them. We will discuss how DAGs can be very instructive about causal inference for researchers planning their own research, or understanding others', by helping identify the conditions for valid causal inference given a research question. Overall, the goal is for the audience to gain a new perspective on causal inference that will help them do good research.
Friday January 26
12:00 PM EDT (New York), 5:00 PM BST (London)
Bayesian Analysis
Dr. Andreas Schwab
Iowa State University
Abstract
This webcast will offer an insightful introduction to Bayesian analysis, a method of empirical data examination that applies Bayes' theorem to update existing knowledge about model parameters based on newly collected data. The webcast will cover the following topics:
- The Basics: Understand the fundamental conceptual nature of Bayesian approaches and their potential advantages over statistical significance tests.
- Parameter Estimation: Conceptually outline the steps of Bayesian parameter estimation, applying Markov-Chain Monte Carlo simulations.
- Prior Distributions: Discuss the function and value of prior distributions in Bayesian analyses.
- Posterior Distributions: Learn how to interpret Bayesian posterior distributions for hypothesis testing, prediction, and theory building.
- Communication and Reporting: Learn about the standards for communicating and reporting Bayesian analyses and results for publication in top management journals.
While the webcast will mention various software packages available for Bayesian analyses, it will not delve into the intricacies of related analytic choices and their coding during Bayesian estimation processes. Instead, the focus is on equipping participants with a basic conceptual understanding of Bayesian analysis, its benefits for hypothesis testing and theory building, and providing actionable advice on conducting and publishing high-quality Bayesian management studies. This webcast is a must-attend for those seeking to enhance their understanding and application of Bayesian analysis in management studies.
AOM members can access the events through the following steps:
- Sign into your AO account.
- Click on your name at the top.
- In the information area click the CARMA globe logo.
- When prompted click "Access CARMA" button.
- This button will take you to Affiliate Program Access page.
- On the Access page follow the instructions for accessing live events.
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Larry Williams
Professor
Texas Tech University
Lincoln NE
(806) 834-1479
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