The Rasch Model from the Perspective of the Representational Theory of Measurement

Kyngdon, Andrew

doi:10.1177/0959354307086924

Cited by 38 publications

(44 citation statements)

References 61 publications

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“…It has frequently been posited that the Rasch model is a probabilistic formulation of additive conjoint measurement (Keats, 1967, G. Fischer, 1968, Brogden, 1977, Karabatsos, 2000. Kyngdon (2008b) disagrees with this assessment, however, and Michell (2008a) gives additional reasons one should be wary of conflating the two. Michell makes the point that merely fitting the Rasch model does not then guarantee that all the benefits of conjoint measurement appear, a stance very much in line with the approach I take.…”

Section: The Rasch Model As a Philosophically Distinct Traditionmentioning

confidence: 93%

“…Michell makes the point that merely fitting the Rasch model does not then guarantee that all the benefits of conjoint measurement appear, a stance very much in line with the approach I take. Even if the approaches to measurement are not equivalent, they are synonymous in enough respects for both Kyngdon (2008b) and Michell (2008a) to suggest that conjoint measurement may be a framework worth considering by those working with the Rasch model.…”

Section: The Rasch Model As a Philosophically Distinct Traditionmentioning

confidence: 99%

“…In the classical framework, the number 2 would be defined as the ratio of these rod's lengths. Although being aware of this distinction is important since it is the impetus for representational measurement, I will not focus in great detail on the conflicting roles of number here (see Kyngdon, 2008b or the critique in Michell, 1990, p. 46-49 for accounts on how the role of number matters in psychometrics).…”

Section: Representational Measurementmentioning

confidence: 99%

“…This dissertation focused on inducing item-side distortions, but the same could be done with person-side distortions. Kyngdon (2008b) My work on item-side distortions is not exhaustive. Depending on the nature of the test, distortions related to local dependence or multidimensionality may be of interest.…”

Section: Future Researchmentioning

confidence: 99%

“…Philosophical distinctions between RM and ACM Although previous scholars have noted the similarities between the ACM and the Rasch model, Kyngdon (2008b) can detect the joint effect of certain levels of ability and item difficulty via the observed proportion of individuals at the specified ability level who answered an item at a given difficulty correctly.…”

Section: 52mentioning

confidence: 99%

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Evaluating the Equal-Interval Hypothesis with Test Score Scales

Domingue

2013

Psychometrika

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DateThe final copy of this thesis has been examined by the signatories, and we find that both the content and the form meet acceptable presentation standards of scholarly work in the above mentioned discipline. In this dissertation, an improved version of Karabatsos's methodology is applied to simulated and empirical data to test whether such data are consistent with the axioms.It is first shown that the methodology behaves reasonably using data simulated to meet the cancellation axioms of ACM. It is then shown that the methodology is capable of distinguishing data simulated to meet the axioms from data that is not. In particular, it is demonstrated that the methodology is sensitive to item-side violations of the axioms. Empirical examples are then used to illustrate the fact that test score data may or may not conform to the ACM axioms. Empirical demonstration shows that an existing test scale thought to satisfy the ACM axioms using the Karabatsos (2001) approach does not do so using the modified approach here.Since not all data may meet the ACM axioms (and hence not warrant interval interpretations), this dissertation also examines whether scale distortions can lead to erroneous conclusions. At the score-level, an approach was developed using "difference matrices" to highlight the fact that when the Rasch (1960) model is applied to certain non-Rasch data, the estimates will be more compressed at lower abilities. This same phenomena was noted in two simulations meant to capture how educational assessment data is used-with respect to schools and educational interventionsiv although the effects of the distortions were small. DedicationDedicated to my family. And brevity.vi

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Section: The Rasch Model As a Philosophically Distinct Traditionmentioning

confidence: 93%

Section: The Rasch Model As a Philosophically Distinct Traditionmentioning

confidence: 99%

Section: Representational Measurementmentioning

confidence: 99%

Section: Future Researchmentioning

confidence: 99%

Section: 52mentioning

confidence: 99%

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Evaluating the Equal-Interval Hypothesis with Test Score Scales

Domingue

2013

Psychometrika

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The Role of Construct Specification Equations and Entropy in the Measurement of Memory

Melin

Pendrill

2022

Springer Series in Measurement Science and Technology

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Memory ability, together with many other constructs related to disability and quality of life, is of growing interest in the social sciences, psychology and in health care examinations. This chapter will focus on two elements aiming at understanding, predicting, measuring and quality-assuring constructs with examples from memory measurements: (i) explicit methods for testing theories of the measurement mechanism and establishment of metrological standards and (ii) substantive theories explaining the constructs themselves. Building on entropy as a principal explanatory variable, analogous to its use in thermodynamics and information theory, we demonstrate how more fit-for-purpose and valid memory measurements can be enabled. Firstly, memory task difficulty, extracted from a Rasch psychometric analysis of memory measurements of experimental data such as from the European NeuroMET project, can be explained with a construct specification equation (CSE). Based on that understanding, the CSE can facilitate the establishment of objective and scalable units through the generation of novel certified reference “materials” for metrological traceability and comparability. These formulations of CSEs can also guide how best to compose new memory metrics, through a judicious choice of items from various legacy tests guided by entropy-based equivalence, which opens up opportunities for formulating new, less onerous but more sensitive and representative tests. Finally, we propose and demonstrate how to formulate CSEs for person ability, correlated statistically and clinically with sets of biomarkers, that can be a means of providing diagnostic information to enhance clinical decisions and targeted interventions.

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From Model to Measurement with Dichotomous Items

Burdick

Stenner

Kyngdon

2022

Explanatory Models, Unit Standards, and Personalized Learning in Educational Measurement

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Psychometric models typically represent encounters between persons and dichotomous items as a random variable with two possible outcomes, one of which can be labeled success. For a given item, the stipulation that each person has a probability of success defines a construct on persons. This model specification defines the construct, but measurement is not yet achieved. The path to measurement must involve replication; unlike coin-tossing, this cannot be attained by repeating the encounter between the same person and the same item. Such replication can only be achieved with more items whose features are included in the model specifications. That is, the model must incorporate multiple items. This chapter examines multi-item model specifications that support the goal of measurement. The objective is to select the model that best facilitates the development of reliable measuring instruments. From this perspective, the Rasch model has important features compared to other models.

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The Rasch Model from the Perspective of the Representational Theory of Measurement

Cited by 38 publications

References 61 publications

Evaluating the Equal-Interval Hypothesis with Test Score Scales

Evaluating the Equal-Interval Hypothesis with Test Score Scales

The Role of Construct Specification Equations and Entropy in the Measurement of Memory

From Model to Measurement with Dichotomous Items

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