Trivariate Theory of Mind Data Analysis with a Conditional Joint Modeling Approach

Minjeong Jeon (), Paul Boeck, Xiangrui Li and Zhong-Lin Lu
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Minjeong Jeon: University of California, Los Angeles
Paul Boeck: Ohio State University
Xiangrui Li: Ohio State University
Zhong-Lin Lu: New York University

Psychometrika, 2020, vol. 85, issue 2, No 8, 398-436

Abstract: Abstract Theory of mind (ToM) is an essential social-cognitive ability to understand one’s own and other people’s mental states. Neural data as well as behavior data have been utilized in ToM research, but the two types of data have rarely been analyzed together, creating a large gap in the literature. In this paper, we propose and apply a novel joint modeling approach to analyze brain activations with two types of behavioral data, response times and response accuracy, obtained from a multi-item ToM assessment, with the intention to shed new light on the nature of the underlying process of ToM reasoning. Our trivariate data analysis suggested that different levels or kinds of processes might be involved during the ToM assessment, which seem to differ in terms of cognitive efficiency and sensitivity to ToM items and the correctness of item responses. Additional details on the trivariate data analysis results are provided with discussions on their implications for ToM research.

Keywords: theory of mind; trivariate data; joint modeling; conditional dependence; response accuracy; response time; fMRI activations (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s11336-020-09710-9

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