ERIC Number: EJ983216
Record Type: Journal
Publication Date: 2012-Oct
Pages: 23
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0033-3123
EISSN: N/A
Modeling Associations among Multivariate Longitudinal Categorical Variables in Survey Data: A Semiparametric Bayesian Approach
Tchumtchoua, Sylvie; Dey, Dipak K.
Psychometrika, v77 n4 p670-692 Oct 2012
This paper proposes a semiparametric Bayesian framework for the analysis of associations among multivariate longitudinal categorical variables in high-dimensional data settings. This type of data is frequent, especially in the social and behavioral sciences. A semiparametric hierarchical factor analysis model is developed in which the distributions of the factors are modeled nonparametrically through a dynamic hierarchical Dirichlet process prior. A Markov chain Monte Carlo algorithm is developed for fitting the model, and the methodology is exemplified through a study of the dynamics of public attitudes toward science and technology in the United States over the period 1992-2001. (Contains 5 tables and 7 figures.)
Descriptors: Factor Analysis, Bayesian Statistics, Behavioral Sciences, Social Sciences, Markov Processes, Longitudinal Studies, Surveys, Public Opinion, Sciences, Technology, Scientific Attitudes, Attitude Measures, Psychometrics, Models, Data Analysis, Nonparametric Statistics, Correlation
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Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
Audience: N/A
Language: English
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Authoring Institution: N/A
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