In judgmental standard setting experiments, it may be difficult to specify subjective probabilities that adequately take the properties of the items into account. As a result, these probabilities are not consistent with each other in the sense that they do not refer to the same borderline level of performance. Methods to check standard setting data for intrajudge inconsistencies are thus of paramount importance to setting meaningful standards. This paper presents a method of consistency analysis for standard setting experiments in which judges specify probabilities for each response alternative of the items. The method is based on a residual diagnosis of the subjective probabilities under the hypothesis of a consistent judge to the probabilities. An empirical example shows how the method can be used to identify sources of inconsistency in response alternatives, items, or judges. (Contains 19 references.) (SLD)
Authors
Related Organizations
- Authorizing Institution
- Twente Univ., Enschede (Netherlands). Faculty of Educational Science and Technology.
- Peer Reviewed
- F
- Publication Type
- Reports - Descriptive
- Published in
- United States of America
Table of Contents
- Detecting Intrajudge Inconsistency in Standard Setting 3
- Wim J. van der Linden 3
- The authors are indebted to the National Institute of Educational Measurement 3
- Citogroep Arnhem The Netherlands for making available the data set in the 3
- Booklet A. Likewise in an Angoff 1971 experiment a judge may specify higher 5
- It is the purpose of this paper to introduce a method for analyzing intrajudge 5
- 1 ... m2. A separate notation is 6
- - 5 7
- - 8 10
- 11-1 E pgij 10
- N-1mi 10
- N mi 10
- The latter explanation can be rejected if the analysis is based 13
- It is not known if this trend generalizes to other content domains. 14
- R. Ben-Yashar S. Nitzan H.J. Vos Optimal Cutoff Points in Single and 22
- R.R. Meijer Diagnosing Item Score Patterns using IRT Based Person-Fit 22
- E.M.L.A. van Krimpen-Stoop R.R. Meijer CUSUM-Based Person-Fit 23
- J.P. Fox C.A.W. Glas Multi-level IRT with Measurement Error in the 23
- A.A. Beguin C.A.W. Glas MCMC Estimation of Multidimensional IRT 23