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Trikalinos, Thomas A.; Hoaglin, David C.; Small, Kevin M.; Terrin, Norma; Schmid, Christopher H. – Research Synthesis Methods, 2014
Existing methods for meta-analysis of diagnostic test accuracy focus primarily on a single index test. We propose models for the joint meta-analysis of studies comparing multiple index tests on the same participants in paired designs. These models respect the grouping of data by studies, account for the within-study correlation between the tests'…
Descriptors: Meta Analysis, Diagnostic Tests, Accuracy, Comparative Analysis
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Wothke, Werner; Burket, George; Chen, Li-Sue; Gao, Furong; Shu, Lianghua; Chia, Mike – Journal of Educational and Behavioral Statistics, 2011
It has been known for some time that item response theory (IRT) models may exhibit a likelihood function of a respondent's ability which may have multiple modes, flat modes, or both. These conditions, often associated with guessing of multiple-choice (MC) questions, can introduce uncertainty and bias to ability estimation by maximum likelihood…
Descriptors: Educational Assessment, Item Response Theory, Computation, Maximum Likelihood Statistics
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Suh, Youngsuk; Bolt, Daniel M. – Psychometrika, 2010
Nested logit item response models for multiple-choice data are presented. Relative to previous models, the new models are suggested to provide a better approximation to multiple-choice items where the application of a solution strategy precedes consideration of response options. In practice, the models also accommodate collapsibility across all…
Descriptors: Computation, Simulation, Psychometrics, Models
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van Barneveld, Christina – Alberta Journal of Educational Research, 2003
The purpose of this study was to examine the potential effect of false assumptions regarding the motivation of examinees on item calibration and test construction. A simulation study was conducted using data generated by means of several models of examinee item response behaviors (the three-parameter logistic model alone and in combination with…
Descriptors: Simulation, Motivation, Computation, Test Construction