A colleague writes:
"I've proposed a Rasch analysis, not a Classical analysis, but people here are not familiar with it and they are not very open to other perspectives than Classical Test Theory (CTT). I've try to explain to them all the advantages of Rasch, but they said: "This is to complicated and people won't understand it. We need a Classical Analysis." But on another project, people were very critical about Rasch and proposed instead a 3-PL model."
Comment: Yes, familiar methods are difficult to unseat. The astrolabe was still being used 150 years after Isaac Newton demonstrated better methods of locating the planets. Classical methods usually survive until a situation arises they can't deal with, such as missing data, adaptive tests, maintaining criterion-based pass-fail points, test-equating with small samples ...
Advocating the 3-PL model means that they expect their students to guess answers at random - so that the student measures will have a chaotic component, lowering the predictive validity of the test. They also expect their items to differ widely in discrimination - which means they expect their item writers to write deficient items, lowering the construct validity of the test.
The 3-P logistic model was designed to model messy data. According to Martha Stocking, an advocate of 3-PL, "Building statistical models is just like this. You take a real situation with real data, messy as this is, and build a model that works to explain the behavior of real data." New York Times, 2-10-2000.
Instead of designing a descriptive model, such as 3-PL, to explain messy data, Georg Rasch designed a model that demands useful data and points out where the data is messy. Messy data produces messy findings. Useful data produces useful findings. But most statisticians believe that the data, however messy, always tells the truth. The problem is that the messy data's "truth" may not be the truth that we need for decision-making.
Rasch: Too Complicated or Too Simple?, Rasch Measurement Transactions, 2006, 20:3 p. 1065
Rasch Publications | ||||
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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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