There are three stages of development through which a new idea is brought into use. This is the pattern by which the Rasch model has been developed into a useful tool for the construction of tests.
The first stage was the application of the idea that Rasch encapsulated in his model. His neat and clean probabilistic model, which strongly represents the essence of what Item Response Theory is intended to do, was an essential measurement insight and a decisive departure from traditional testing. Application of the Model generally produced reasonable results. But there were some problematic ones. In Portland,we could not link tests a full grade level apart in difficulty in a way which satisfied us.
In the second stage we paid attention to the conditions under which the model functions successfully. We found that with our Portland data it took 300 cases and 40 items to stabilize item calibrations. We ran into trouble when we tried to link tests more than three tenths of a logit apart in difficulty. However, we still believed that fit statistics and individual standard errors were all we needed to know. This was a hangover from years of statistical training, understandable but inadequate for the task ahead. We experienced a period of maturing, and of finding out through trial and error that the Rasch model requires test developers to think clearly and comprehensively.
The third phase emerges as a discontinuity. It arises from the ashes of conventional statistical methodology like a Phoenix - a new way of incorporating old ideas into unforeseen contexts. This third phase requires thought processes compatible with the nature of the model as probably measuring a variable.
Probabilistic thinking must replace deterministic ideas in the intrinsic beauty of the relationship expressed by the theory. Deterministic thinking vilifies randomness as destructive, though inevitable. It follows that randomness must be minimized. Probabilistic thinking, however, perceives randomness to be constructive. Randomness is like wind, fire and water: too much or too little are bad. A healthy variable requires a harmonious amount. Deterministic thinking looks for yes/no directives based on significance tests. Probabilistic thinking looks for reasonable patterns and useful compromises.
The power and the sensitivity of the Rasch model is apparent when judging an item's compatibility with a variable and the relationship of each item to the others in the test instrument. When linking tests, selection of meaningful linking items and their calibrations requires good judgement, not just statistical know-how. This same judgmental procedure is necessary to build an item bank.
Rasch practitioners, I exhort you! Abandon the hopeless quest for deterministic perfection. Decide instead to construct meaning and utility. That construction is often found to have greater beauty and to yield more insight than perfection could have ever offered. "To travel hopefully is a better thing than to arrive" (Robert Louis Stevenson, Virginibus Puerisque: El Dorado.)
3708 NE 136 Place
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The journey to knowledge. Ingebo G. Rasch Measurement Transactions, 1996, 10:2 p. 508
|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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