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ERIC Number: EJ832814
Record Type: Journal
Publication Date: 2009-Apr
Pages: 23
Abstractor: As Provided
ISSN: ISSN-1743-727X
A Preliminary Bayesian Analysis of Incomplete Longitudinal Data from a Small Sample: Methodological Advances in an International Comparative Study of Educational Inequality
Hsieh, Chueh-An; Maier, Kimberly S.
International Journal of Research & Method in Education, v32 n1 p103-125 Apr 2009
The capacity of Bayesian methods in estimating complex statistical models is undeniable. Bayesian data analysis is seen as having a range of advantages, such as an intuitive probabilistic interpretation of the parameters of interest, the efficient incorporation of prior information to empirical data analysis, model averaging and model selection. As a simplified demonstration, we illustrate (1) how Bayesians test and compare two non-nested growth curve models using Bayesian estimation with non-informative prior; (2) how Bayesians model and handle missing outcomes in the context of missing values; and (3) how Bayesians incorporate data-based evidence from a previous data set, construct informative priors and treat them as extra information while conducting an up-to-date analogy analysis. (Contains 7 tables, 5 figures, and 5 notes.)
Routledge. 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