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Autor/inn/enMacCallum, Robert C.; Edwards, Michael C.; Cai, Li
TitelHopes and Cautions in Implementing Bayesian Structural Equation Modeling
QuelleIn: Psychological Methods, 17 (2012) 3, S.340-345 (6 Seiten)
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN1082-989X
DOI10.1037/a0027131
SchlagwörterStellungnahme; Structural Equation Models; Bayesian Statistics; Computation; Expertise; Goodness of Fit; Monte Carlo Methods; Markov Processes; Factor Analysis; Problems
AbstractMuthen and Asparouhov (2012) have proposed and demonstrated an approach to model specification and estimation in structural equation modeling (SEM) using Bayesian methods. Their contribution builds on previous work in this area by (a) focusing on the translation of conventional SEM models into a Bayesian framework wherein parameters fixed at zero in a conventional model can be respecified using small-variance priors and (b) implementing their approach in software that is widely accessible. We recognize potential benefits for applied researchers as discussed by Muthen and Asparouhov, and we also see a tradeoff in that effective use of the proposed approach introduces increased demands in terms of expertise of users to navigate new complexities in model specification, parameter estimation, and evaluation of results. We also raise cautions regarding the issues of model modification and model fit. Although we see significant potential value in the use of Bayesian SEM, we also believe that effective use will require an awareness of these complexities. (Contains 1 figure and 12 footnotes.) (As Provided).
AnmerkungenAmerican Psychological Association. Journals Department, 750 First Street NE, Washington, DC 20002-4242. Tel: 800-374-2721; Tel: 202-336-5510; Fax: 202-336-5502; e-mail: order@apa.org; Web site: http://www.apa.org/publications
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2017/4/10
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