Hierarchical Bayesian Modeling for Test Theory Without an Answer Key

Zita Oravecz (), Royce Anders and William Batchelder

Psychometrika, 2015, vol. 80, issue 2, 364 pages

Abstract: Cultural Consensus Theory (CCT) models have been applied extensively across research domains in the social and behavioral sciences in order to explore shared knowledge and beliefs. CCT models operate on response data, in which the answer key is latent. The current paper develops methods to enhance the application of these models by developing the appropriate specifications for hierarchical Bayesian inference. A primary contribution is the methodology for integrating the use of covariates into CCT models. More specifically, both person- and item-related parameters are introduced as random effects that can respectively account for patterns of inter-individual and inter-item variability. Copyright The Psychometric Society 2015

Keywords: Cultural Consensus Theory; Bayesian statistics; hierarchical model; covariate modeling (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/s11336-013-9379-4

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