Objectivity, realism, and psychometrics

Trisha Nowland*, Alissa Beath, Simon Boag

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    1 Citation (Scopus)

    Abstract

    The aim of this paper is raise and address questions regarding the status of objectivity for the generalized latent variable model (GLVM) in psychometric research, given the conceptual, logical and mathematical problems of circularity, conditional independence, and factor indeterminacy, respectively. The question of objectivity for the model is examined with respect to measurement and realist perspectives. Drawing on insights from measurement and systems dynamics literature, a proposal for a conceptual framework is presented, that integrates: i) inference from the best systematisation; and ii) axiomatic set theory. This conceptual framework, which addresses the whole of a research project, invites specification of the expected relations, conditions, and assumptions which are relevant to the implementation of the GLVM. While this does not eliminate the problems for the GLVM, it provides future researchers with maximal objective information in standardized form, supporting minimization of definitional and instrumental uncertainty, in psychological modelling practices.

    Original languageEnglish
    Pages (from-to)292-299
    Number of pages8
    JournalMeasurement: Journal of the International Measurement Confederation
    Volume145
    DOIs
    Publication statusPublished - Oct 2019

    Keywords

    • psychometrics
    • generalised latent variable model
    • conceptual framework
    • set theory

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