Bayesian Analysis of Ordinal Survey Data Using the Dirichlet Process to Account for Respondent Personality Traits |
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Authors: | Saman Muthukumarana Tim B Swartz |
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Institution: | 1. Department of Statistics , University of Manitoba , Winnipeg, Manitoba , Canada;2. Department of Statistics and Actuarial Science , Simon Fraser University , Burnaby, British Columbia , Canada |
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Abstract: | This article presents a Bayesian latent variable model used to analyze ordinal response survey data by taking into account the characteristics of respondents. The ordinal response data are viewed as multivariate responses arising from continuous latent variables with known cut-points. Each respondent is characterized by two parameters that have a Dirichlet process as their joint prior distribution. The proposed mechanism adjusts for classes of personalities. The model is applied to student survey data in course evaluations. Goodness-of-fit (GoF) procedures are developed for assessing the validity of the model. The proposed GoF procedures are simple, intuitive, and do not seem to be a part of current Bayesian practice. |
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Keywords: | Dirichlet process Goodness-of-fit Latent variables MCMC WinBUGS |
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