Separating models, ideas, and data to avoid a paradox: Rejoinder to Humphry

Sijtsma, Klaas; Emons, Wilco H. M.

doi:10.1177/0959354313503724

Cited by 5 publications

(16 citation statements)

References 23 publications

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“…521–523). As Sijtsma and Emons (2013) suggest, we need to distinguish (a) the psychometric model, (b) the theory concerning the mental attribute, and (c) empirical data, which cannot on its own validate the measure. Measurement is a social activity (Fisher, 2003).…”

Section: A Practical Approach To Measuring a Constructmentioning

confidence: 99%

“…It is precisely these subjective and heuristic choices that need to be explained, discussed, and justified that we find in the approaches based on warranted assertibility proposed by Dewey. “Data cannot show that a model is wrong” (Sijtsma & Emons, 2013, p. 788), so this empirical validation needs to be linked to the theory before reaching warranted assertability for the measure, not proof, but a set of facts enabling us to consider that a quantitative measure can be used.…”

Section: A Practical Approach To Measuring a Constructmentioning

confidence: 99%

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Measurement, ontology, and epistemology: Psychology needs pragmatism-realism

Guyon

Kop

Juhel

et al. 2018

Theory & Psychology

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Measurement in psychology is at the heart of a major debate in the academic literature. We aim to contribute to a critical discussion of this issue. We propose to reposition the object of this type of measure, namely a mental attribute as measured by mental tests. Mental attributes should be considered not as a true object independent of the knower, but as an emergent property of a person dependent on the social context. On the basis of this clarified ontology, we consider that an empirical approach to measuring a mental attribute is possible. This approach must be resolutely pragmatist and realist. In practical terms, this means that a test needs to be renegotiated relative to the context. The validation of quantitative measures requires verification of a certain number of criteria. Consequently, our work critically explores measures as they are usually implemented in the area of psychometrics.

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Section: A Practical Approach To Measuring a Constructmentioning

confidence: 99%

Section: A Practical Approach To Measuring a Constructmentioning

confidence: 99%

Measurement, ontology, and epistemology: Psychology needs pragmatism-realism

Guyon

Kop

Juhel

et al. 2018

Theory & Psychology

View full text Add to dashboard Cite

show abstract

“…Similarly, I fully support Michell's (2014) recommendation for the "critical as opposed to credulous use" (p. 115) of IRT models. Sijtsma and Emons (2013) express the view that the realization of laws in psychology is light years away. My response to this is twofold.…”

Section: Pathological Sciencementioning

confidence: 99%

Psychological measurement: Theory, paradoxes, and prototypes

Humphry

2017

Theory & Psychology

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The article focuses on the ongoing debate regarding the measurement of psychological attributes. The aim is to clarify different uses of the term theory and key points of agreement and disagreement among participants. In addition, the article addresses misinterpretations of key points in recent articles and notes an apparent paradox arising in the representational theory of measurement. Substantive theory is contrasted with both item response theory and the representational theory of measurement. Emphasis is placed on the direct dependence of the measurement of physical attributes on substantive quantitative theory as opposed to any form of separate measurement theory. It is concluded that the primary challenge faced in quantitative psychology is to posit testable substantive theories or laws which form a foundation for measurement.

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“…If measurement-oriented work in the human sciences were following the lead of physical metrology, one might expect to see primacy given in such work to developing and refining theory, concepts, laws, models, units and instrumentation with primary consideration of these phenomena. However, standard practices in the human sciences, and educational measurement in particular, often instead gives primacy to the formalisms of latent variable (and, in particular, item response) models, which are applied to item and test scores, as prescriptions for the phenomena under investigation (Maraun, 2007;Sijtsma & Emons, 2013). For example, item response models prescribe that test behaviour is necessarily a stochastic process involving a quantitative property of students (e.g., reading comprehension ability).…”

Section: Introductionmentioning

confidence: 99%

The human sciences, models and metrological mythology

McGrane

2020

Measurement

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Measurement concepts and vocabulary have become commonplace in the human sciences. To this end, the field of educational measurement has largely concerned itself with the development and use of a family of mathematical, "psychometric" models collectively known as latent variable models. These models contain parameters that are commonly interpreted as referring to properties of individuals and test items, and estimates of these parameters are accordingly interpreted as measured values of these properties. Such interpretations are based on the erroneous assumption that the correspondence between these parameters and properties has been substantiated, whereas the educational measurement literature and discourse frequently conflates or confuses the two; different instantiations of a pervasive representational fallacy. This fallacy drives an unscientific approach to modelling where the nature of educational phenomena and their causal role in measurement is ignored. To advance beyond the mythology of "latent variables", the human sciences need to eradicate this fallacy and establish scientific models for measurement. The human sciences, models and metrological mythology "The tendency has always been strong to believe that whatever receives a name must be an entity or being, having an independent existence of its own..." (Mill, 1878, p.5) "It is no longer a question of imitation, nor duplication, nor even parody. It is a question of substituting the signs of the real for the real…" (Baudrillard, 1994, p.2

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Separating models, ideas, and data to avoid a paradox: Rejoinder to Humphry

Cited by 5 publications

References 23 publications

Measurement, ontology, and epistemology: Psychology needs pragmatism-realism

Measurement, ontology, and epistemology: Psychology needs pragmatism-realism

Psychological measurement: Theory, paradoxes, and prototypes

The human sciences, models and metrological mythology

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