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Jia, Yue; Stokes, Lynne; Harris, Ian; Wang, Yan – Educational Testing Service, 2011
Estimation of parameters of random effects models from samples collected via complex multistage designs is considered. One way to reduce estimation bias due to unequal probabilities of selection is to incorporate sampling weights. Many researchers have been proposed various weighting methods (Korn, & Graubard, 2003; Pfeffermann, Skinner,…
Descriptors: Computation, Statistical Bias, Sampling, Statistical Analysis
Moses, Tim; Miao, Jing; Dorans, Neil – Educational Testing Service, 2010
This study compared the accuracies of four differential item functioning (DIF) estimation methods, where each method makes use of only one of the following: raw data, logistic regression, loglinear models, or kernel smoothing. The major focus was on the estimation strategies' potential for estimating score-level, conditional DIF. A secondary focus…
Descriptors: Test Bias, Statistical Analysis, Computation, Scores
Livingston, Samuel A.; Lewis, Charles – Educational Testing Service, 2009
This report proposes an empirical Bayes approach to the problem of equating scores on test forms taken by very small numbers of test takers. The equated score is estimated separately at each score point, making it unnecessary to model either the score distribution or the equating transformation. Prior information comes from equatings of other…
Descriptors: Test Length, Equated Scores, Bayesian Statistics, Sample Size