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The Complementarity of Psychometrics and the Representational Theory of Measurement

Bibliographic Data

ID8399604
AuthorsElina Vessonen (0000-0002-5931-6267, University of Cambridge, corresponding author)
Year2020
Volume71
Issue2
Pages415-442
Publication date2020-06-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueThe British Journal for the Philosophy of Science (JOURNAL)
Journal identifiersISSN: 0007-0882 • E-ISSN: 1464-3537
PublisherOxford University Press (PUBLISHER • GB)
DOI10.1093/bjps/axy032
OpenAlexW2791909319
LanguageEN
Citations received4
References cited44

Psychometrics and the representational theory of measurement (RTM) are widely used in social scientific measurement. They are currently pursued largely in isolation from one another. I argue that despite their separation in practice, RTM and psychometrics are complementary approaches, because they can contribute in complementary ways to the establishment of what I argue is a crucial measurement property, namely, representational interpretability. Because RTM and psychometrics are complementary in the establishment of representational interpretability, the current separation of measurement approaches is unfounded. 1. Introduction 2. Two Approaches to Measurement 2.1. Representational theory of measurement 2.2. Psychometrics 2.3. Representational interpretability 3. Complementarity, Conceptually 3.1. Representational theory of measurement: Conditions of representational interpretability 3.2. Psychometrics: Evidence of representational interpretability 4. Complementarity in Action 4.1. What is the Rasch model? 4.2. Rasch and conjoint measurement 5. Conclusion: Critics and Fruits of Complementarity

Complementarity (molecular biology) · Developmental psychology · Epistemology · Interpretability · Item response theory · Psychometrics · Rasch model · Artificial Intelligence · Computer Science · Mental Health Research Topics · Philosophy · Philosophy and History of Science · Psychology · Social Representations and Identity

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Unique citing works4
Citations per year0,57
Citation span2019 - 2026 (8)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 2

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