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Clauser, Jerome C.; Hambleton, Ronald K.; Baldwin, Peter – Educational and Psychological Measurement, 2017
The Angoff standard setting method relies on content experts to review exam items and make judgments about the performance of the minimally proficient examinee. Unfortunately, at times content experts may have gaps in their understanding of specific exam content. These gaps are particularly likely to occur when the content domain is broad and/or…
Descriptors: Scores, Item Analysis, Classification, Decision Making
Lyren, Per-Erik; Hambleton, Ronald K. – International Journal of Testing, 2011
The equal ability distribution assumption associated with the equivalent groups equating design was investigated in the context of a selection test for admission to higher education. The purpose was to assess the consequences for the test-takers in terms of receiving improperly high or low scores compared to their peers, and to find strong…
Descriptors: Evidence, Test Items, Ability Grouping, Item Response Theory
Hambleton, Ronald K. – New Directions for Testing and Measurement, 1980
Latent trait models provide a new scale for reporting educational and psychological measurements. Characteristics, interpretations, and uses of these scales are considered. (Author/RL)
Descriptors: Goodness of Fit, Latent Trait Theory, Mathematical Models, Measurement Techniques
Hambleton, Ronald K.; Rogers, H. Jane – 1986
This report was designed to respond to two major methodological shortcomings in the item bias literature: (1) misfitting test models; and (2) the use of significance tests. Specifically, the goals of the research were to describe a newly developed method known as the "plot method" for identifying potentially biased test items and to…
Descriptors: Criterion Referenced Tests, Culture Fair Tests, Difficulty Level, Estimation (Mathematics)

And Others; Hambleton, Ronald K. – Review of Educational Research, 1978
Topics concerning latent trait theory are addressed: (1) dimensionality of latent space, local independence, and item characteristic curves; (2) models--equations, parameter estimation, testing assumptions, and goodness of fit, (3) applications test developments, item bias, tailored testing and equating; and (4) advantages over classical…
Descriptors: Ability, Bayesian Statistics, Goodness of Fit, Item Analysis