Showing 1 - 5 of 5 Research Library Publications
Posted: | Peter Baldwin

Educational Measurement: Issues and Practice

 

This article aims to answer the question: when the assumption that examinees may apply themselves fully yet still respond incorrectly is violated, what are the consequences of using the modified model proposed by Lewis and his colleagues? 

Posted: | B. E. Clauser, M. Kane, J. C. Clauser

Journal of Educational Measurement: Volume 57, Issue 2, Pages 216-229

 

This article presents two generalizability-theory–based analyses of the proportion of the item variance that contributes to error in the cut score. For one approach, variance components are estimated on the probability (or proportion-correct) scale of the Angoff judgments, and for the other, the judgments are transferred to the theta scale of an item response theory model before estimating the variance components.

Posted: | B.C. Leventhal, I. Grabovsky

Educational Measurement: Issues and Practice, 39: 30-36

 

This article proposes the conscious weight method and subconscious weight method to bring more objectivity to the standard setting process. To do this, these methods quantify the relative harm of the negative consequences of false positive and false negative misclassification.

Posted: | P. Baldwin, M.J. Margolis, B.E. Clauser, J. Mee, M. Winward

Educational Measurement: Issues and Practice, 39: 37-44

 

This article presents the results of an experiment in which content experts were randomly assigned to one of two response probability conditions: .67 and .80. If the standard-setting judgments collected with the bookmark procedure are internally consistent, both conditions should produce highly similar cut scores.

Posted: | M. von Davier

Measurement: Interdisciplinary Research and Perspectives, 16:1, 59-70

 

This article critically reviews how diagnostic models have been conceptualized and how they compare to other approaches used in educational measurement. In particular, certain assumptions that have been taken for granted and used as defining characteristics of diagnostic models are reviewed and it is questioned whether these assumptions are the reason why these models have not had the success in operational analyses and large-scale applications, contrary to what many have hoped.