Showing 1 - 5 of 5 Research Library Publications
Posted: | Chunyan Liu, Daniel Jurich

Applied Psychological Measurement: Volume 46, issue 6, page(s) 529-547

 

The current simulation study demonstrated that the sampling variance associated with the item response theory (IRT) item parameter estimates can help detect outliers in the common items under the 2-PL and 3-PL IRT models. The results showed the proposed sampling variance statistic (SV) outperformed the traditional displacement method with cutoff values of 0.3 and 0.5 along a variety of evaluation criteria.

Posted: | Peter Baldwin, Brian E. Clauser

Journal of Educational Measurement: Volume 59, Issue 2, Pages 140-160

 

A conceptual framework for thinking about the problem of score comparability is given followed by a description of three classes of connectives. Examples from the history of innovations in testing are given for each class.

Posted: | Y.S. Park, A. Morales, L. Ross, M. Paniagua

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).

Posted: | M. von Davier, J. H. Shin, L. Khorramdel, L. Stankov

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.

Posted: | Z. Jiang, M.R. Raymond

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.