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Modeling Associations Among Multivariate Longitudinal Categorical Variables in Survey Data: A Semiparametric Bayesian Approach

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  • Sylvie Tchumtchoua
  • Dipak Dey

Abstract

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. Copyright The Psychometric Society 2012

Suggested Citation

  • Sylvie Tchumtchoua & Dipak Dey, 2012. "Modeling Associations Among Multivariate Longitudinal Categorical Variables in Survey Data: A Semiparametric Bayesian Approach," Psychometrika, Springer;The Psychometric Society, vol. 77(4), pages 670-692, October.
    • Handle: RePEc:spr:psycho:v:77:y:2012:i:4:p:670-692
    DOI: 10.1007/s11336-012-9274-4
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    References listed on IDEAS

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    1. Teh, Yee Whye & Jordan, Michael I. & Beal, Matthew J. & Blei, David M., 2006. "Hierarchical Dirichlet Processes," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1566-1581, December.
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    5. Hee‐Je Bak, 2001. "Education and Public Attitudes toward Science: Implications for the “Deficit Model” of Education and Support for Science and Technology," Social Science Quarterly, Southwestern Social Science Association, vol. 82(4), pages 779-795, December.
    6. A. Bhattacharya & D. B. Dunson, 2011. "Sparse Bayesian infinite factor models," Biometrika, Biometrika Trust, vol. 98(2), pages 291-306.
    7. Mingan Yang & David Dunson, 2010. "Bayesian Semiparametric Structural Equation Models with Latent Variables," Psychometrika, Springer;The Psychometric Society, vol. 75(4), pages 675-693, December.
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