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Qian, Jiahe – ETS Research Report Series, 2020
The finite population correction (FPC) factor is often used to adjust variance estimators for survey data sampled from a finite population without replacement. As a replicated resampling approach, the jackknife approach is usually implemented without the FPC factor incorporated in its variance estimates. A paradigm is proposed to compare the…
Descriptors: Computation, Sampling, Data, Statistical Analysis
Jewsbury, Paul A. – ETS Research Report Series, 2019
When an assessment undergoes changes to the administration or instrument, bridge studies are typically used to try to ensure comparability of scores before and after the change. Among the most common and powerful is the common population linking design, with the use of a linear transformation to link scores to the metric of the original…
Descriptors: Evaluation Research, Scores, Error Patterns, Error of Measurement
Wang, Lin; Qian, Jiahe; Lee, Yi-Hsuan – ETS Research Report Series, 2018
Educational assessment data are often collected from a set of test centers across various geographic regions, and therefore the data samples contain clusters. Such cluster-based data may result in clustering effects in variance estimation. However, in many grouped jackknife variance estimation applications, jackknife groups are often formed by a…
Descriptors: Item Response Theory, Scaling, Equated Scores, Cluster Grouping
Kane, Michael T. – ETS Research Report Series, 2017
By aggregating residual gain scores (the differences between each student's current score and a predicted score based on prior performance) for a school or a teacher, value-added models (VAMs) can be used to generate estimates of school or teacher effects. It is known that random errors in the prior scores will introduce bias into predictions of…
Descriptors: Error of Measurement, Value Added Models, Scores, Teacher Effectiveness
Kim, Sooyeon; Moses, Tim; Yoo, Hanwook Henry – ETS Research Report Series, 2015
The purpose of this inquiry was to investigate the effectiveness of item response theory (IRT) proficiency estimators in terms of estimation bias and error under multistage testing (MST). We chose a 2-stage MST design in which 1 adaptation to the examinees' ability levels takes place. It includes 4 modules (1 at Stage 1, 3 at Stage 2) and 3 paths…
Descriptors: Item Response Theory, Computation, Statistical Bias, Error of Measurement
Moses, Tim; Holland, Paul – ETS Research Report Series, 2008
The purpose of this paper is to extend von Davier, Holland, and Thayer's (2004b) framework of kernel equating so that it can incorporate raw data and traditional equipercentile equating methods. One result of this more general framework is that previous equating methodology research can be viewed more comprehensively. Another result is that the…
Descriptors: Equated Scores, Error of Measurement, Statistical Analysis, Computation
Oranje, Andreas; Li, Deping; Kandathil, Mathew – ETS Research Report Series, 2009
Several complex sample standard error estimators based on linearization and resampling for the latent regression model of the National Assessment of Educational Progress (NAEP) are studied with respect to design choices such as number of items, number of regressors, and the efficiency of the sample. This paper provides an evaluation of the extent…
Descriptors: Error of Measurement, Computation, Regression (Statistics), National Competency Tests
Haberman, Shelby J. – ETS Research Report Series, 2008
The reliability of a scaled score can be computed by use of item response theory. Estimated reliability can be obtained even if the item response model selected is not valid.
Descriptors: Reliability, Scores, Item Response Theory, Computation
Li, Deping; Oranje, Andreas; Jiang, Yanlin – ETS Research Report Series, 2007
The hierarchical latent regression model (HLRM) is a flexible framework for estimating group-level proficiency while taking into account the complex sample designs often found in large-scale educational surveys. A complex assessment design in which information is collected at different levels (such as student, school, and district), the model also…
Descriptors: Hierarchical Linear Modeling, Regression (Statistics), Computation, Comparative Analysis
Kim, Sooyeon; Linvingston, Samuel A.; Lewis, Charles – ETS Research Report Series, 2008
This paper describes an empirical evaluation of a Bayesian procedure for equating scores on test forms taken by small numbers of examinees, using collateral information from the equating of other test forms. In this procedure, a separate Bayesian estimate is derived for the equated score at each raw-score level, making it unnecessary to specify a…
Descriptors: Equated Scores, Statistical Analysis, Sample Size, Bayesian Statistics
Lee, Yi-Hsuan; Zhang, Jinming – ETS Research Report Series, 2008
The method of maximum-likelihood is typically applied to item response theory (IRT) models when the ability parameter is estimated while conditioning on the true item parameters. In practice, the item parameters are unknown and need to be estimated first from a calibration sample. Lewis (1985) and Zhang and Lu (2007) proposed the expected response…
Descriptors: Item Response Theory, Comparative Analysis, Computation, Ability
Moses, Tim; Holland, Paul – ETS Research Report Series, 2007
The purpose of this study was to empirically evaluate the impact of loglinear presmoothing accuracy on equating bias and variability across chained and post-stratification equating methods, kernel and percentile-rank continuization methods, and sample sizes. The results of evaluating presmoothing on equating accuracy generally agreed with those of…
Descriptors: Equated Scores, Statistical Analysis, Accuracy, Sample Size
Zhang, Jinming; Lu, Ting – ETS Research Report Series, 2007
In practical applications of item response theory (IRT), item parameters are usually estimated first from a calibration sample. After treating these estimates as fixed and known, ability parameters are then estimated. However, the statistical inferences based on the estimated abilities can be misleading if the uncertainty of the item parameter…
Descriptors: Item Response Theory, Ability, Error of Measurement, Maximum Likelihood Statistics
Antal, Tamás – ETS Research Report Series, 2007
Full account of the latent regression model for the National Assessment of Educational Progress is given. The treatment includes derivation of the EM algorithm, Newton-Raphson method, and the asymptotic standard errors. The paper also features the use of the adaptive Gauss-Hermite numerical integration method as a basic tool to evaluate…
Descriptors: Regression (Statistics), Item Response Theory, National Competency Tests, Evaluation Methods
Braun, Henry; Qian, Jiahe – ETS Research Report Series, 2008
This report describes the derivation and evaluation of a method for comparing the performance standards for public school students set by different states. It is based on an approach proposed by McLaughlin and associates, which constituted an innovative attempt to resolve the confusion and concern that occurs when very different proportions of…
Descriptors: State Standards, Comparative Analysis, Public Schools, National Competency Tests
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