Bayesian Cultural Consensus Theory
- Author(s): Oravecz, Z
- Vandekerckhove, J
- Batchelder, WH
- et al.
Published Web Locationhttps://doi.org/10.1177/1525822X13520280
© The Author(s) 2014. 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.
Many UC-authored scholarly publications are freely available on this site because of the UC Academic Senate's Open Access Policy. Let us know how this access is important for you.