title: Cultural Consensus Theory for the ordinal data case.
abstract: A Cultural Consensus Theory approach for ordinal data is developed, leading to a new model for ordered polytomous data. The model introduces a novel way of measuring response biases and also measures consensus item values, a consensus response scale, item difficulty, and informant knowledge. The model is extended as a finite mixture model to fit both simulated and real multicultural data, in which subgroups of informants have different sets of consensus item values. The extension is thus a form of model-based clustering for ordinal data. The hierarchical Bayesian framework is utilized for inference, and two posterior predictive checks are developed to verify the central assumptions of the model.
authors: University of California, Irvine, USA, andersr@uci.edu.
authors: Royce
authors: R
authors: Anders
authors: William H
authors: WH
authors: Batchelder
mesh_terms: D001499:Bayes Theorem; D003627:Data Interpretation, Statistical; D006801:Humans; D008962:Models, Theoretical; D011594:Psychometrics / Q000379:methods*; D017603:Signal Detection, Psychological