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Direct linkMcNeish, Daniel – Review of Educational Research, 2017
In education research, small samples are common because of financial limitations, logistical challenges, or exploratory studies. With small samples, statistical principles on which researchers rely do not hold, leading to trust issues with model estimates and possible replication issues when scaling up. Researchers are generally aware of such…
Descriptors: Models, Statistical Analysis, Sampling, Sample Size
Koziol, Natalie A. – Applied Measurement in Education, 2016
Testlets, or groups of related items, are commonly included in educational assessments due to their many logistical and conceptual advantages. Despite their advantages, testlets introduce complications into the theory and practice of educational measurement. Responses to items within a testlet tend to be correlated even after controlling for…
Descriptors: Classification, Accuracy, Comparative Analysis, Models
Paek, Insu; Wilson, Mark – Educational and Psychological Measurement, 2011
This study elaborates the Rasch differential item functioning (DIF) model formulation under the marginal maximum likelihood estimation context. Also, the Rasch DIF model performance was examined and compared with the Mantel-Haenszel (MH) procedure in small sample and short test length conditions through simulations. The theoretically known…
Descriptors: Test Bias, Test Length, Statistical Inference, Geometric Concepts
Finkelman, Matthew David – Applied Psychological Measurement, 2010
In sequential mastery testing (SMT), assessment via computer is used to classify examinees into one of two mutually exclusive categories. Unlike paper-and-pencil tests, SMT has the capability to use variable-length stopping rules. One approach to shortening variable-length tests is stochastic curtailment, which halts examination if the probability…
Descriptors: Mastery Tests, Computer Assisted Testing, Adaptive Testing, Test Length
Beauducel, Andre; Herzberg, Philipp Yorck – Structural Equation Modeling: A Multidisciplinary Journal, 2006
This simulation study compared maximum likelihood (ML) estimation with weighted least squares means and variance adjusted (WLSMV) estimation. The study was based on confirmatory factor analyses with 1, 2, 4, and 8 factors, based on 250, 500, 750, and 1,000 cases, and on 5, 10, 20, and 40 variables with 2, 3, 4, 5, and 6 categories. There was no…
Descriptors: Factor Analysis, Maximum Likelihood Statistics, Classification, Sample Size
Yang, Xiangdong; Poggio, John C.; Glasnapp, Douglas R. – Educational and Psychological Measurement, 2006
The effects of five ability estimators, that is, maximum likelihood estimator, weighted likelihood estimator, maximum a posteriori, expected a posteriori, and Owen's sequential estimator, on the performances of the item response theory-based adaptive classification procedure on multiple categories were studied via simulations. The following…
Descriptors: Classification, Computation, Simulation, Item Response Theory
