Just a reminder about the two back-to-back PDWs on Bayesian Methods at the upcoming Academy of Management Conference in Boston, MA. No pre-registration is required, and we look forward to having you along to discuss exciting advents in the area of Bayesian Methods. The details for the two PDWs are as follows:
PDW #1 Title: Why We All Should Be Bayesians!
Time: Saturday, August 4, 2012 at 10:15 AM – 12:15 PM
Location: Westin Copley, Room: Great Republic
Presenters: David Krackhardt (Carnegie Mellon University), William H. Starbuck (University of Oregon), Michael J. Zyphur (University of Melbourne), Andreas Schwab (Iowa State University)
Abstract:
This workshop introduces management researchers to the opportunities of Bayesian statistics for empirical research in the management sciences. We will outline the fundamental features of the Bayesian method without delving into the mathematical details. Instead, we will first outline the conceptual differences and potential advantages of a Bayesian approach compared to traditional statistical analyses involving null-hypothesis significance tests (NHSTs). We will then show examples from empirical management research that illustrates Bayesian data analysis. Finally, we will discuss why in spite of strong arguments supporting the use of Bayesian statistics, the field of management research has been very reluctant considering Bayesian analysis as an alternative. The purpose of this workshop is to convince participants of the potential opportunities Bayesian methods can provide and to encourage organizational researchers to apply these methods in future research.
PDW #2 Title: Bayesian and Frequentist Research Methods: Theory, History, Estimation, Application, and Integration
Time: Saturday, August 4, 2012 at 12:45 AM – 2:45 PM
Location: Westin Copley, Room: St. George C & D
Presenters: Michael J. Zyphur (University of Melbourne), Dean Pierides (University of Melbourne)
Abstract:
This workshop introduces a Bayesian theory of probability for inductive inference in organization and management science. Currently, a frequentist theory dominates. The difference between the two theories is that Bayesian probability references a degree of belief in a proposition or state of affairs, while frequentist probability references the relative frequency of an observation or event in an infinite series of observations or events. The foundations of Bayesian and frequentist probability will be described, as well as their histories, methods of estimation, targets for application, and how they can both be used to greatly expand the potential for rigorous and relevant research. Estimation will be conducted in the popular statistics program Mplus. Program code, datasets, and interpretations of results will be incorporated into the workshop, including decision-theoretic foundations of making inductive inferences using different theories of probability.
Andreas
Andreas Schwab, Ph.D.
Management Department
3315 Gerdin Business Building
Ames, IA 50011-1350
515-294 -8119
aschwab@iastate.edu
andreas.schwab9 (skype)
http://www.business.iastate.edu/faculty/aschwab