
RESEARCH LIBRARY
RESEARCH LIBRARY
View the latest publications from members of the NBME research team
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?
Evaluation & the Health Professions: Volume: 43 issue: 3, page(s): 149-158
This study examines the innovative and practical application of DCM framework to health professions educational assessments using retrospective large-scale assessment data from the basic and clinical sciences: National Board of Medical Examiners Subject Examinations in pathology (n = 2,006) and medicine (n = 2,351).
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.
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.
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.
Applied Psychological Measurement: Volume: 42 issue: 4, page(s): 291-306
The research presented in this article combines mathematical derivations and empirical results to investigate effects of the nonparametric anchoring vignette approach proposed by King, Murray, Salomon, and Tandon on the reliability and validity of rating data. The anchoring vignette approach aims to correct rating data for response styles to improve comparability across individuals and groups.
Applied Psychological Measurement: Volume: 42 issue: 8, page(s): 595-612
Conventional methods for evaluating the utility of subscores rely on reliability and correlation coefficients. However, correlations can overlook a notable source of variability: variation in subtest means/difficulties. Brennan introduced a reliability index for score profiles based on multivariate generalizability theory, designated as G, which is sensitive to variation in subtest difficulty. However, there has been little, if any, research evaluating the properties of this index. A series of simulation experiments, as well as analyses of real data, were conducted to investigate G under various conditions of subtest reliability, subtest correlations, and variability in subtest means.