TY - JOUR
T1 - Bayesian Cultural Consensus Theory
AU - Oravecz, Zita
AU - Vandekerckhove, Joachim
AU - Batchelder, William H.
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: We gratefully acknowledge support from research grants from the Air Force Office of Scientific Research (AFOSR) and the Army Research Office (ARO) to Batchelder, PI.
Publisher Copyright:
© The Author(s) 2014.
PY - 2014/8/1
Y1 - 2014/8/1
N2 - 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.
AB - 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.
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U2 - 10.1177/1525822X13520280
DO - 10.1177/1525822X13520280
M3 - Article
AN - SCOPUS:84907207129
SN - 1525-822X
VL - 26
SP - 207
EP - 222
JO - Field Methods
JF - Field Methods
IS - 3
ER -