Title: Bayesian Model Averaging: Theoretical developments and practical applications Authors: Jacob Montgomery, Brendan Nyhan Entrydate: 2008-01-22 17:43:17 Keywords: Bayesian model averaging, BMA, model robustness, specification uncertainty Abstract: Political science researchers typically conduct an idiosyncratic search of possible model configurations and then present a single specification to readers. This approach systematically understates the uncertainty of our results, generates concern among readers and reviewers about fragile model specifications, and leads to the estimation of bloated models with huge numbers of controls. Bayesian model averaging (BMA) offers a systematic method for analyzing specification uncertainty and checking the robustness of one's results to alternative model specifications. In this paper, we summarize BMA, review important recent developments in BMA research, and argue for a different approach to using the technique in political science. We then illustrate the methodology by reanalyzing models of voting in U.S. Senate elections and international civil war onset using software that respects statistical conventions within political science. http://polmeth.wustl.edu/retrieve.php?id=730 ********************************************************** Political Methodology E-Mail List Editors: Melanie Goodrich, <[log in to unmask]> Delia Bailey, <[log in to unmask]> ********************************************************** Send messages to [log in to unmask] To join the list, cancel your subscription, or modify your subscription settings visit: http://polmeth.wustl.edu/polmeth.php **********************************************************