Review of Rasch Models: Foundations, Recent Developments, Applications

Surely editors Gerhard Fischer and Ivo Molenaar will be pleased to learn that our academic bookstore shelved their volume in the Mathematics section. RM:FRDA (1995, New York: Springer) reflects their interest in the Rasch model as an elegant mathematical formulation with many fascinating properties. But this is far from what motivated Georg Rasch to invent his models. For him, utility was the lynch-pin.

"Rasch Models" is an accurate start to the book's title, because RM:FRDA is definitely not about Rasch measurement. It explicitly states that its Rasch Models are IRT models (p. 4), i.e., descriptions of empirical data with measurement properties that follow from empirical test (p. 12, in a section dependent on, but not referencing, S.S. Stevens). In contrast, Rasch measurement is entirely, indeed oppositely, different. Rasch measurement is a prescriptive methodology for constructing and maintaining objective linear measures. The practitioner's goal is to devise methods for collecting data that fit the model, in order to obtain inferentially stable linear measures, and so ultimately to construct useful meaning.

"Foundations"? This brings to mind Plato, Newton, Heidegger, Thorndike, Thurstone, Guttman, Luce & Tukey..., and their modern commentators, George Engelhard, Jr. and William P. Fisher, Jr. Almost none are mentioned. Thank you, Henk Kelderman (p. 307-309) for including just a soupçon of that philosophy whose general absence caused Erling Andersen to be "very disappointed" (p. 389).

The "Foundations", to which Gerhard Fischer, a distinguished pioneer in Rasch methodology, particularly devotes himself, are the type of niceties that fascinate mathematical theorists. Those laying these "Foundations" include authors familiar to us from Psychometrika. They focus on model formulation, estimation methods and goodness-of-fit tests. Erling Andersen diagnoses their disassociation from the real measurement challenge: "It is often overlooked that the main reason for applying a latent structure model is not to estimate the item parameters, but to estimate the value of the latent variable for a given individual or for a group of individuals" (p. 286).

"Recent Developments" refers to novel model parameterizations rather than to computer-adaptive testing, performance assessment, self-measuring KeyMath-style forms,... The main recent development according to RM:FRDA seems to be the discovery that all other recent developments are merely refinements of earlier developments. It is certainly true that the automobile is merely a refined application of Newton's Laws of Motion, but does that prevent it from being important in its own right?

Practitioners, do not be deceived by the word "Applications" in the title, for there is nothing here for you. Chapter 7, "Test Construction from Item Banks" may look promising, but its elaborate technique could be replaced, with advantage, by one good item map.

The first goal of RM:FRDA mentioned in the "Preface" is that of overcoming the inaccessibility of knowledge about the Rasch model. RM:FRDA does not achieve this goal. Standard texts that are not referenced include Wright & Stone (1978) Best Test Design; Andrich (1988) Rasch Models for Measurement; and Bruce Choppin on Measurement and Education (1985, Evaluation in Education 9:1). Further, how is it possible to present "an overview of the various approaches to testing model fit" (p. 69) and fail to reference Richard Smith? In fact, to find accessible knowledge about the Rasch model, start with a search of the Social Sciences Citation Index database looking for material citing Rasch-G, followed by a search of the ERIC database looking for the word Rasch, and then search every other available database to see what other "Recent Developments" have happened!

The Preface also reveals a decisive shortcoming in RM:FRDA. Although the editors say they invited "a number of outstanding authors in the field to contribute" (and the roster of authors is of the highest caliber), it turns out that "none of the editors and authors is a native English speaker." This tragic limitation leaves one wondering: Did all American and Australian scholars decline their invitations, or were they simply not invited?

Erling Andersen's "In Retrospect" is the gem of the book. It contains vignettes about Georg Rasch's life. It explains Rasch's philosophical basis, his concern with basic measurement problems in all sciences, his disinterest in chi-square tests and estimator consistency, his focus on individuals, his animosity to the normal distribution, his delight with graphical techniques. Let us encourage Fischer and Molenaar to turn this Retrospect into a preview of their next volume.

John Michael Linacre

Linacre J.M. (1995) Review of Rasch Models: Foundations, Recent Developments and Applications. G. H. Fischer and I. Molenaar (Eds.). Rasch Measurement Transactions, 9(2), p.428.

Rasch-Related Resources: Rasch Measurement YouTube Channel
Rasch Measurement Transactions & Rasch Measurement research papers - free	An Introduction to the Rasch Model with Examples in R (eRm, etc.), Debelak, Strobl, Zeigenfuse	Rasch Measurement Theory Analysis in R, Wind, Hua	Applying the Rasch Model in Social Sciences Using R, Lamprianou	El modelo métrico de Rasch: Fundamentación, implementación e interpretación de la medida en ciencias sociales (Spanish Edition), Manuel González-Montesinos M.
Rasch Models: Foundations, Recent Developments, and Applications, Fischer & Molenaar	Probabilistic Models for Some Intelligence and Attainment Tests, Georg Rasch	Rasch Models for Measurement, David Andrich	Constructing Measures, Mark Wilson	Best Test Design - free, Wright & Stone Rating Scale Analysis - free, Wright & Masters
Virtual Standard Setting: Setting Cut Scores, Charalambos Kollias	Diseño de Mejores Pruebas - free, Spanish Best Test Design	A Course in Rasch Measurement Theory, Andrich, Marais	Rasch Models in Health, Christensen, Kreiner, Mesba	Multivariate and Mixture Distribution Rasch Models, von Davier, Carstensen
Rasch Books and Publications: Winsteps and Facets
Applying the Rasch Model (Winsteps, Facets) 4th Ed., Bond, Yan, Heene	Advances in Rasch Analyses in the Human Sciences (Winsteps, Facets) 1st Ed., Boone, Staver	Advances in Applications of Rasch Measurement in Science Education, X. Liu & W. J. Boone	Rasch Analysis in the Human Sciences (Winsteps) Boone, Staver, Yale	Appliquer le modèle de Rasch: Défis et pistes de solution (Winsteps) E. Dionne, S. Béland
Introduction to Many-Facet Rasch Measurement (Facets), Thomas Eckes	Rasch Models for Solving Measurement Problems (Facets), George Engelhard, Jr. & Jue Wang	Statistical Analyses for Language Testers (Facets), Rita Green	Invariant Measurement with Raters and Rating Scales: Rasch Models for Rater-Mediated Assessments (Facets), George Engelhard, Jr. & Stefanie Wind	Aplicação do Modelo de Rasch (Português), de Bond, Trevor G., Fox, Christine M
Exploring Rating Scale Functioning for Survey Research (R, Facets), Stefanie Wind	Rasch Measurement: Applications, Khine	Winsteps Tutorials - free Facets Tutorials - free	Many-Facet Rasch Measurement (Facets) - free, J.M. Linacre	Fairness, Justice and Language Assessment (Winsteps, Facets), McNamara, Knoch, Fan

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