Bayesian Cultural Consensus Theory. Issue 3 (August 2014)

• Record Type: Journal Article
• Authors: Oravecz, Zita; Vandekerckhove, Joachim; Batchelder, William H.
• Is Part Of: Field methods. Volume 26:Issue 3(2014:Aug.)
• Page Start: 207
• Page End: 222
• Publication Date: 2014-08
• Subjects: cultural consensus theory -- Bayesian inference -- user-friendly software -- dichotomous response data; Ethnology -- Methodology -- Periodicals; Anthropology -- Methodology -- Periodicals; Anthropologie -- Méthodologie -- Périodiques; 306.072
• DOI: 10.1177/1525822X13520280
• Languages: English
• ISSNs: 1525-822X

Abstract

In this article, we present a Bayesian inference framework for cultural consensus theory (CCT) models for dichotomous (True/False) response data and provide an associated, user-friendly software package along with a detailed user's guide to carry out the inference. We believe that the time is ripe for Bayesian statistical inference to become the default choice in the field of CCT. Unfortunately, a lack of publications presenting a practical description of the Bayesian framework in the context of CCT models as well as a dearth of accessible software to apply Bayesian inference to CCT data has so far prevented this from happening. We introduce the Bayesian treatment of several CCT models, focusing on the various merits of Bayesian parameter estimation and interpretation of results, and also introduce the Bayesian Cultural Consensus Toolbox software package.