"All human observation is a mushy matter of opinion, except in so far as cogent argument constrains that opinion. To understand measurement and error is to be freed from superstitions.
"The first thing we should observe is that theory and measurement are more intimately related than is often thought. Theory, untestable and irrefutable theory, pervades even the most elementary forms of direct measurement. More importantly, the most sophisticated theoretical structures can be regarded as frameworks for systematic measurement. The lesson to be learned from this, particularly in the mental and social sciences, is that, however cleverly, we measure something, however reliable the test or reproducible the measurement, without a theoretical framework into which that quantity enters, it is useless. One can devise reproducible measures of quantities without end - but without a theoretical structure we have only a relatively useless oddity. I say `relatively' because even such measures do have their uses in communication; even without much theory, intelligence tests are handy for locating students in the spectrum of brightness, and passing that information along.
"A corollary to this is that the development of measures and the testing of theories is often approached in the wrong order. Because we have been told so often that we should let the data speak for themselves, that we should avoid preconceptions, and that we should also provide rigorous quantitative tests of our hypotheses, we may be tempted to put the cart before the horse. We may think that we must develop good solid operational measuring instruments, whose application exhibits high interpersonal uniformity, before we can give our imaginations rein to develop hypotheses and theories for subsequent testing. The development of measures for quantities - indeed, the development of quantities themselves - must go hand in hand with the development of the theoretical structures in which those qunatities play a role. It is the whole system of theory and quantity that allows us to augment the predictive observational content of our bodies of knowledge."
These insights come from Henry E. Kyburg Jr. in Theory and Measurement (Cambridge: Cambridge University Press, 1984). Though unaware of Rasch measurement, he addresses the issues which concern us - sometimes mathematically, sometimes philosophically and sometimes anecdotally. There are gems of wisdom strewn throughout this book.
Kyburg on Mush Rasch Measurement Transactions, 1991, 5:1 p. 132
Please help with Standard Dataset 4: Andrich Rating Scale Model
|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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