title: Moving in Parallel Toward a Modern Modeling Epistemology: Bayes Factors and Frequentist Modeling Methods.
abstract: The Bayesian-frequentist debate typically portrays these statistical perspectives as opposing views. However, both Bayesian and frequentist statisticians have expanded their epistemological basis away from a singular focus on the null hypothesis, to a broader perspective involving the development and comparison of competing statistical/mathematical models. For frequentists, statistical developments such as structural equation modeling and multilevel modeling have facilitated this transition. For Bayesians, the Bayes factor has facilitated this transition. The Bayes factor is treated in articles within this issue of Multivariate Behavioral Research. The current presentation provides brief commentary on those articles and more extended discussion of the transition toward a modern modeling epistemology. In certain respects, Bayesians and frequentists share common goals.
authors.affiliation: a Department of Psychology and Human Development , Vanderbilt University.
authors.forename: Joseph Lee
authors.initials: JL
authors.lastname: Rodgers
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D001699:Biometry; D002986:Clinical Trials as Topic; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D019359:Knowledge; D008433:Mathematics; D015233:Models, Statistical; D012107:Research Design
keywords: Bayes factor; Bayesian methods; frequentist methods; statistical modeling