Quotations - Rasch Measurement Transactions, Fall 2001, 15:2

Measurement Requires Explanation

"To the extent that validation is properly characterized as involving interpretations and inferences about scores, clearly the properties of scores are central to validation. More specifically, it is the properties of scale scores [measures] that are of principal concern, because it is scale scores, not raw scores, that are used to make decisions. It is unfortunate that most of the literature about validation fails to make explicit this distinction. For the most part, it is scale scores, not raw scores, that are the lens through which test users indirectly observe the student behavior elicited by a test or assessment. As such, I believe that validation is clearly inadequate without clear explanations of scale scores, which necessarily involves well-reasoned defenses of the assumptions involved in scaling. Further, these explanations should be made in a manner that is understandable to test users and policy-makers. Test users should not be required or expected to blindly accept scaling results.

"It is eminently clear that scaling usually involves complex statistical operations. It is much less recognized that scaling often necessitates choosing among value-laden assumptions. Such choices should not be made in a psychometric vacuum; rather, they should be heavily informed by practice. I believe the role of scaling in drawing inferences about test scores is one of the most neglected aspects of validation, and the notion that scaling is (or should be) solely a psychometric matter may be the single most widely held misconception about measurement."

Robert L. Brennan (1998) Misconceptions at the intersection of measurement theory and practice. Educational Measurement: Issues and Practice. 17:1, 8.

Oversimplification

"The invention of deliberately oversimplified theories is one of the major techniques of science, particularly of the `exact' sciences, which make extensive use of mathematical analysis. If a biophysicist can usefully employ simplified models of the cell and the cosmologist simplified models of the universe then we can reasonably expect that simplified games may prove to be useful models for more complicated conflicts."
John Williams, The Compleat Strategyst. New York: McGraw Hill, 1954.

And we can also reasonably expect that simplified representations of complex interpersonal relationships, attitudes, abilities, performances, etc., will also prove useful, as has in fact been repeatedly demonstrated by Rasch measurement.William P. Fisher, Jr.


Quotations Florin R.E. … Rasch Measurement Transactions, 2001, 15:2 p.822



Rasch Books and Publications
Invariant Measurement: Using Rasch Models in the Social, Behavioral, and Health Sciences, 2nd Edn. George Engelhard, Jr. & Jue Wang 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
Introduction to Many-Facet Rasch Measurement (Facets), Thomas Eckes 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 Appliquer le modèle de Rasch: Défis et pistes de solution (Winsteps) E. Dionne, S. Béland
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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
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