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ERIC Number: EJ966292
Record Type: Journal
Publication Date: 2012
Pages: 14
Abstractor: As Provided
ISSN: ISSN-1070-5511
Small Sample Properties of Bayesian Multivariate Autoregressive Time Series Models
Price, Larry R.
Structural Equation Modeling: A Multidisciplinary Journal, v19 n1 p51-64 2012
The aim of this study was to compare the small sample (N = 1, 3, 5, 10, 15) performance of a Bayesian multivariate vector autoregressive (BVAR-SEM) time series model relative to frequentist power and parameter estimation bias. A multivariate autoregressive model was developed based on correlated autoregressive time series vectors of varying lengths (T = 25, 50, 75, 100, 125) using Statistical Analysis System (SAS) version 9.2. Autoregressive components for the 5 series vectors included coefficients of 0.80, 0.70, 0.65, 0.50 and 0.40. Error variance components included values of 0.20, 0.20, 0.10, 0.15, and 0.15, with cross-lagged coefficients of 0.10, 0.10, 0.15, 0.10, and 0.10. A Monte Carlo study revealed that in comparison to frequentist methods, the Bayesian approach provided increased sensitivity for hypothesis testing and detecting Type I error. (Contains 5 tables and 1 figure.)
Psychology Press. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site:
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A