"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.
"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 Measurement Transactions (free, online)||Rasch Measurement research papers (free, online)||Probabilistic Models for Some Intelligence and Attainment Tests, Georg Rasch||Applying the Rasch Model 3rd. Ed., Bond & Fox||Best Test Design, Wright & Stone|
|Rating Scale Analysis, Wright & Masters||Introduction to Rasch Measurement, E. Smith & R. Smith||Introduction to Many-Facet Rasch Measurement, Thomas Eckes||Invariant Measurement: Using Rasch Models in the Social, Behavioral, and Health Sciences, George Engelhard, Jr.||Statistical Analyses for Language Testers, Rita Green|
|Rasch Models: Foundations, Recent Developments, and Applications, Fischer & Molenaar||Journal of Applied Measurement||Rasch models for measurement, David Andrich||Constructing Measures, Mark Wilson||Rasch Analysis in the Human Sciences, Boone, Stave, Yale|
|in Spanish:||Análisis de Rasch para todos, Agustín Tristán||Mediciones, Posicionamientos y Diagnósticos Competitivos, Juan Ramón Oreja Rodríguez|
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|July 30 - Nov., 2018||Online Introduction to Classical and Rasch Measurement Theories (D.Andrich), University of Western Australia, Perth, Australia, http://www.education.uwa.edu.au/ppl/courses|
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