A Rasch Critic Answers Himself

Complaint: "Rasch's one-parameter logistic model promised item calibration independent of the sample, and scoring of individuals independent of the set of items on which they have been tested. The implication of strong comparability among scores turned out to be a mirage, not least because the model proved rather fussy about which sorts of data it would fit. As Rasch himself reported in this journal (Rasch, 1966), the model did not work for a verbal analogies test or for an analogue of Raven's matrices, two of the stalwarts of psychometric practice." (p. 182-3)

Desire: "The challenge is to recover the element of surprise - astonishment even - which greeted the developments of the first decades of this century (1900-1909) when effective psychological measurement was first demonstrated. For too long test theory has concerned itself with ever cleverer accounts of unimproved practical effectiveness and not with recommendations as to how to devise more effective tests." (p. 183)

Blinkhorn S.F. (1997) Past imperfect, future conditional: fifty years of test theory. British Jnl of Mathematical and Statistical Psychology, 50, 175-185.

Comment: The Rasch model specifies ideals toward which constructors of more effective tests must strive. As the model operationalizes these ideals, it is "fussy" about data, and so necessarily criticizes the unimproved "stalwarts of psychometric practice". Nevertheless, Rasch practitioners are continually delighted to discover that apparently incoherent data can be coerced into constructing coherent, useful measures on clearly articulated linear variables.

Blinkhorn, S.F. A Rasch Critic Answers Himself. … Rasch Measurement Transactions, 2000, 14:3 p.770

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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