Juggling Judging Ambiguity

A continuing practical problem in rating performances is eliminating ambiguity introduced by deficient judging plans. A recent conference aired data in this form:

          Judge  A    Judge B
Items:   P  Q  R      P  Q  R
Person:          Task X
101      2  2  1      3  1  2
102      3  2  2
103      2  3  2      2  3  2
104      4  3  3      3  3  3
           Task Y
201      3  2  3
202      3  3  3      2  2  2
203      4  3  3
204      4  4  3      3  3  4

At first glance, all seems well. The three items, P, Q, R, can be in one frame of reference, because they share the same judge-person-task combinations. The two judges, A, B, can be in the same frame of reference, because they rate every second person together. Now comes the problem. The persons seem to share the same frame of reference because so many of them are rated on the same tasks. But there are two tasks. Why are the four 100-group people rated lower on Task X than the four 200-group people on Task Y? Are the 100-group people less able than the 200-group? Is Task X is harder than Task Y? These data cannot say which!

Resolving this ambiguity requires perception and decision. The first step is to notice the problem. If you detect it during data collection, a slight change to the judging plan can remedy the situation. For instance, some people could be asked to perform both tasks. Nevertheless, continue to be on the look out for this ambiguity during analysis. Many statistical procedures fail to report it, and so may produce misleading results.

There are only two choices for resolving this issue: either the tasks are said to be alike or the people are said to be alike. If Task X and Task Y were intended to have the same difficulty, and that still seems a reasonable assertion, then anchor them together at the same calibration. This resolves the ambiguity, and interprets the overall score difference between the 100-group and the 200-group of persons as a difference in ability levels.

On the other hand, you may have intended that the tasks be different by an amount unknown as yet. Then the only solution is to treat the two groups of persons as though they estimate the same mean ability. Specify the analysis to set the mean ability level of the 100-group at the same value as the mean ability level of the 200-group. Now the overall score difference between the 100-group and the 200-group will express a difference in difficulty between Task X and Task Y.

This type of ambiguity is common. It is seen in data where supervisors rate their own trainees. Do good ratings signify good trainees or a lenient rater? It is wise to try both options. First analyze the data as though the supervisors rated equally strictly, then analyze the data as though the groups of trainees were of the same average ability. A comparison of the two analyses frequently implies that the trainees are rather similar (particularly if they are at the end of regular training), but that the supervisors' rating styles are rather different. Who your supervisor is may turn out to be more important than what you accomplish.

Juggling Judging Ambiguity, J Linacre … Rasch Measurement Transactions, 1991, 5:3 p. 167

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

Forum

Rasch Measurement Forum to discuss any Rasch-related topic

Go to Top of Page
Go to index of all Rasch Measurement Transactions
AERA members: Join the Rasch Measurement SIG and receive the printed version of RMT
Some back issues of RMT are available as bound volumes
Subscribe to Journal of Applied Measurement

Go to Institute for Objective Measurement Home Page. The Rasch Measurement SIG (AERA) thanks the Institute for Objective Measurement for inviting the publication of Rasch Measurement Transactions on the Institute's website, www.rasch.org.

The URL of this page is www.rasch.org/rmt/rmt53h.htm

Website: www.rasch.org/rmt/contents.htm