AERA-APA-NCME Standards for Educational and Psychological Testing

teststandards.org tells us: The Standards for Educational and Psychological Testing was developed to "promote the sound and ethical use of tests and to provide a basis for evaluating the quality of testing practices" (AERA, APA, & NCME, 1999, p. 1). The Standards provides criteria for the "evaluation of tests, testing practices, and the effects of test use" (AERA, APA, & NCME, 1999, p. 2).

Comments on the current revision of the Standards are requested by Wednesday, April 20, 2011.

Let me share my thoughts with you ...

There's a fundamentally qualitative difference between measurement standards as they are defined by the AERA-APA-NCME and as they are defined in sciences that prioritize measurement as quantification involving the equal-ratio divisibility of magnitude differences. The Standards, to date, try to control the process with operational recommendations. Standards in the natural sciences, in contrast, focus on the metrics.

The psychosocial sciences focus on process because of the near-universal assumption that quantitative standards like those of the natural sciences are not feasible, notwithstanding 80+ years of theory, data, and calibrated instruments to the contrary. In contrast, the natural sciences do not need to bother with processual recommendations as standards because traceability to reference-standard metrics mediates the way natural laws and theories structure the relation of observations to expectations. Of course, a tape measure or an ammeter must be used correctly, but no one worries about whether the tape measure or the ammeter is itself "fair".

What we need to do is to establish the viability of an alternative form of standards, ones dominated by rigorously articulated and predictive construct theories, instruments calibrated to universally uniform metrics, and data fit to models specifying the requirements for objective inference. Georg Rasch was well aware that his models are, in fact, statements of psychosocial laws (Rasch, 1960, p. 10-11). When data fit a Rasch model, the investigator has effectively discovered a new law, or failed to falsify an existing one.

In summary:

AERA-APA-NCME: Mandated Fairness → Consequence: (Hoped for) Good Measures

Rasch: Constructed Good Measures → Consequence: (Verifiable) Fairness

With the widespread awareness of the dominant paradigm's role in maintaining the status quo in various disciplines, it has become commonplace to observe that the adherents of a paradigm are almost never persuaded to abandon it in favor of another. New paradigms replace old ones as the proponents and adherents of the old one retire and are replaced by people who grew up familiar with the new one (Kuhn, 1962).

My personal body of work is aimed at building up documentation, language, theory, evidence, and instruments that would constitute the beginnings of a history and tradition of measurement research and practice capable of offering an alternative to the status quo of the dominant psychosocial Standards paradigm.

The August 2011 International Measurement Confederation (IMEKO) meeting in Jena, Germany is an opportunity for Rasch measurement theoreticians and practitioners to interact with natural scientists and engineers who are especially attuned to, informed about, and interested in the possibilities for unifying the language, concepts, and practice of measurement across the sciences. The call for papers is available at ... . The submission deadline is Thursday, March 31st, 2011. I hope to see many of you there.

William P. Fisher, Jr.

T. Kuhn (1962) The Structure of Scientific Revolutions. Chicago: Univ. of Chicago Press.



AERA-APA-NCME Standards for Educational and Psychological Testing, W.P. Fisher, Jr. ... Rasch Measurement Transactions, 2011, 24:4, 1310




Rasch Books and Publications
Invariant Measurement: Using Rasch Models in the Social, Behavioral, and Health Sciences, 2nd Edn. George Engelhard, Jr. & Jue Wang 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
Introduction to Many-Facet Rasch Measurement (Facets), Thomas Eckes 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 Appliquer le modèle de Rasch: Défis et pistes de solution (Winsteps) E. Dionne, S. Béland
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
Other 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

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