Objectivity, realism, and psychometrics

•Examines the question of objectivity for latent variable modelling.•Focuses on conditional independence, circularity, and factor indeterminacy.•Proposes a conceptual framework to address problems for objectivity. The aim of this paper is raise and address questions regarding the status of objectivi...

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Veröffentlicht in:Measurement : journal of the International Measurement Confederation 2019-10, Vol.145, p.292-299
Hauptverfasser: Nowland, Trisha, Beath, Alissa, Boag, Simon
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Beath, Alissa
Boag, Simon
description •Examines the question of objectivity for latent variable modelling.•Focuses on conditional independence, circularity, and factor indeterminacy.•Proposes a conceptual framework to address problems for objectivity. 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.
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subjects Conceptual framework
Generalised latent variable model
Objectivity
Psychometrics
Quantitative psychology
Questions
Set theory
Variables
title Objectivity, realism, and psychometrics
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