Do Bad Data Refute Good Theory?

Because of its data-descriptive limitation, Item Response Theory (IRT) practice misrepresents Rasch's models, often under the rubric 1-PL, as simple examples of more complicated approaches. IRT implements confused numeration, mislabeled "measurement". In common with all descriptive statistical techniques, IRT tries to fit models to data. Guided by principles of parameter parsimony, the analyst prefers some models to others, but the data always have the last word.

Georg Rasch saw that the road to science was to fit data to models - a data-prescriptive approach. Careful re-analyses of their laboratory diaries show that Mendeleev (with heredity) and Newton (with laws of motion) also employed this approach. Another recent example is the "search for the top quark".

The IRT perspective appeals to superficial fairness. Whatever happened is the truth! "If the child marked the correct box, for whatever reason, then credit must be given!" This deterministic mindset is not new. It also befuddled some ancient Greeks.

Pythagoras vs. IRT?

Pythagoras' Theorem is a model for constructing and recognizing right-triangles. Whenever the sum of the squares of the two sides of a triangle equal the square of the hypotenuse, we recognize a right-triangle, e.g., the 3-4-5 triangle. The Pythagoreans and their opponents, the Sophists, understood the theorem to hold every time a right-triangle was drawn. Then it was discovered that no degree of measurement precision could make the Pythagorean model exactly match a right isosceles triangle, e.g., 1-1-2. This is because the ratio of 1 and 2 cannot be reduced to a ratio of two integers. The Sophists gloated: "The model doesn't work in practice, so it must be rejected!" The Pythagoreans, distressed, tried to hide this failure.

The flaw in the logic of those ancient Greeks is now obvious. Mathematical theorems are not proven or refuted on the basis of whether or not they fit any particular sample of data produced by any particular experimental apparatus. Though this decisive point has been made repeatedly in the history of science, it remains to be integrated into the methods, knowledge, attitudes, and imaginations of social scientists.

Rasch's Separability Theorem is a model for constructing and recognizing mathematically invariant, unidimensional variables. Any time we see that person parameters can be estimated independently of item parameters, we know invariant unidimensionality has been achieved. IRT proponents, imitating the Sophists, understand the Separability Theorem concretely, as holding for every actual item and person. They claim that, since Rasch's models never exactly describe actual data, they are impractical in the psychosocial sciences. On the other hand, some advocates of the Separability Theorem (Streiner & Norman, 1995) follow the Pythagoreans by attempting to conceal its inevitable failure to describe empirical data.

Paradoxically, Pythagoras' Theorem, though never exactly realized in practice, is highly practical when approximated even crudely. Stepping out a 3-4-5 triangle on the ground gives a good-enough 90 angle for most purposes. Similarly with Rasch's Separability Theorem. Administering a simple test of a few items is often good enough to operationalize a construct and to measure respondents along it.

Pythagoras committed suicide over the apparent malfunction of his model. Rasch, however, dismissed so-called failures of his models as a misunderstanding of their purpose: "On the whole we should not overlook that since a model is never true, but only more or less adequate, deficiencies are bound to show, given sufficient data" (Rasch 1980, 1992, p. 92).

William P. Fisher, Jr.

Fisher W.P. Jr. (1998) Do Bad Data Refute Good Theory? Rasch Measurement Transactions 11:4 p. 600.

Streiner DL, Norman GR (1995) Health Measurement Scales, 2nd Ed. New York: Oxford University Press.

Do Bad Data Refute Good Theory? Fisher W.P. Jr. … Rasch Measurement Transactions, 1998, 11:4 p. 600.




Rasch-Related Resources: Rasch Measurement YouTube Channel
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
Rating Scale Analysis - free, Wright & Masters
Virtual Standard Setting: Setting Cut Scores, Charalambos Kollias Diseño de Mejores Pruebas - free, Spanish Best Test Design A Course in Rasch Measurement Theory, Andrich, Marais Rasch Models in Health, Christensen, Kreiner, Mesba Multivariate and Mixture Distribution Rasch Models, von Davier, Carstensen
Rasch Books and Publications: Winsteps and Facets
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 Appliquer le modèle de Rasch: Défis et pistes de solution (Winsteps) E. Dionne, S. Béland
Introduction to Many-Facet Rasch Measurement (Facets), Thomas Eckes Rasch Models for Solving Measurement Problems (Facets), George Engelhard, Jr. & Jue Wang 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
Exploring Rating Scale Functioning for Survey Research (R, Facets), Stefanie Wind Rasch Measurement: Applications, Khine Winsteps Tutorials - free
Facets Tutorials - free
Many-Facet Rasch Measurement (Facets) - free, J.M. Linacre Fairness, Justice and Language Assessment (Winsteps, Facets), McNamara, Knoch, Fan

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