ERIC Number: EJ883159
Record Type: Journal
Publication Date: 2010
Who Needs Linear Equating under the NEAT Design?
Maris, Gunter; Schmittmann, Verena D.; Borsboom, Denny
Measurement: Interdisciplinary Research and Perspectives, v8 n1 p11-15 2010
Test equating under the NEAT design is, at best, a necessary evil. At bottom, the procedure aims to reach a conclusion on what a tested person would have done, if he or she were administered a set of items that were in fact never administered. It is not possible to infer such a conclusion from the data, because one simply has not made the required observations. Therefore one has to base the inference on strong theoretical claims that are not testable in the NEAT design. As a consequence, the inferences made about people's abilities, and the decisions that are based on these inferences, rest on untested theoretical assumptions. In principle, one should therefore advise against using a NEAT design whenever that can be avoided. In this paper, the authors argue that all equating procedures depend on assumptions regarding the appropriateness and invariance of a measurement model which, if correct, imply that the linear equating procedures are unlikely to work well. In addition, in the case where an invariant latent variable underlies the responses in both groups, that model offers an easier and more justifiable means of equating. The authors conclude that equating methods within the NEAT design are quite problematic in general: if they work, they are not needed, and if they are needed, they do not work.
Descriptors: Equated Scores, Inferences, Item Response Theory, Error of Measurement, Models, Regression (Statistics), Scores, Maximum Likelihood Statistics, Test Wiseness, Evaluation
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Publication Type: Journal Articles; Reports - Evaluative
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