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Joint Bayesian Modeling of Binomial and Rank Data for Primate Cognition

Barney, BJ, Amici, F, Aureli, F, Call, J and Johnson, VE (2015) Joint Bayesian Modeling of Binomial and Rank Data for Primate Cognition. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 110 (510). pp. 573-582. ISSN 0162-1459

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In recent years, substantial effort has been devoted to methods for analyzing data containing mixed response types, but such techniques typically do not include rank data among the response types. Some unique challenges exist in analyzing rank data, particularly when ties are prevalent. We present techniques for jointly modeling binomial and rank data using Bayesian latent variable models. We apply these techniques to compare the cognitive abilities of nonhuman primates based on their performance on 17 cognitive tasks scored on either a rank or binomial scale. To jointly model the rank and binomial responses, we assume that responses are implicitly determined by latent cognitive abilities. We then model the latent variables using random effects models, with identifying restrictions chosen to promote parsimonious prior specification and model inferences. Results from the primate cognitive data are presented to illustrate the methodology. Our results suggest that the ordering of the cognitive abilities of species varies significantly across tasks, suggesting a partially independent evolution of cognitive abilities in primates. Supplementary materials for this article are available online.

Item Type: Article
Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis in JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION on 1 Apr 2015, available online: http://www.tandfonline.com/10.1080/01621459.2015.1016223
Uncontrolled Keywords: 0104 Statistics, 1403 Econometrics
Subjects: G Geography. Anthropology. Recreation > GN Anthropology
Q Science > QL Zoology
Divisions: Natural Sciences & Psychology (closed 31 Aug 19)
Publisher: Taylor & Francis
Related URLs:
Date Deposited: 09 Mar 2016 09:20
Last Modified: 18 May 2022 10:39
DOI or ID number: 10.1080/01621459.2015.1016223
URI: https://researchonline.ljmu.ac.uk/id/eprint/3108
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