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Showing 1 to 15 of 22 results Save | Export
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Martin, Michael O.; Mullis, Ina V. S. – Journal of Educational and Behavioral Statistics, 2019
International large-scale assessments of student achievement such as International Association for the Evaluation of Educational Achievement's Trends in International Mathematics and Science Study (TIMSS) and Progress in International Reading Literacy Study and Organization for Economic Cooperation and Development's Program for International…
Descriptors: Achievement Tests, International Assessment, Mathematics Tests, Science Achievement
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Rutkowski, Leslie – Applied Measurement in Education, 2014
Large-scale assessment programs such as the National Assessment of Educational Progress (NAEP), Trends in International Mathematics and Science Study (TIMSS), and Programme for International Student Assessment (PISA) use a sophisticated assessment administration design called matrix sampling that minimizes the testing burden on individual…
Descriptors: Measurement, Testing, Item Sampling, Computation
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Puhan, Gautam; Moses, Tim; Grant, Mary; McHale, Fred – ETS Research Report Series, 2008
A single group (SG) equating design with nearly equivalent test forms (SiGNET) design was developed by Grant (2006) to equate small volume tests. The basis of this design is that examinees take two largely overlapping test forms within a single administration. The scored items for the operational form are divided into mini-tests called testlets.…
Descriptors: Data Collection, Equated Scores, Item Sampling, Sample Size
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Schumacker, Randall E.; Smith, Everett V., Jr. – Educational and Psychological Measurement, 2007
Measurement error is a common theme in classical measurement models used in testing and assessment. In classical measurement models, the definition of measurement error and the subsequent reliability coefficients differ on the basis of the test administration design. Internal consistency reliability specifies error due primarily to poor item…
Descriptors: Measurement Techniques, Error of Measurement, Item Sampling, Item Response Theory
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Barcikowski, Robert S. – Educational and Psychological Measurement, 1974
Descriptors: Error of Measurement, Item Sampling, Testing Problems
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Pandey, Tej N.; Shoemaker, David M. – Educational and Psychological Measurement, 1975
Described herein are formulas and computational procedures for estimating the mean and second through fourth central moments of universe scores through multiple matrix sampling. Additionally, procedures are given for approximating the standard error associated with each estimate. All procedures are applicable when items are scored either…
Descriptors: Error of Measurement, Item Sampling, Matrices, Scoring Formulas
Pandey, Tej N. – 1975
Standard errors of pooled mean estimate in multiple matrix sampling were compared for two procedures. The data were from tests involving items with and without replacement. The two procedures involve the formulations of Madow and Lord, and Novick; the former permits sampling of item, with or without replacement, whereas the latter is to be used…
Descriptors: Comparative Analysis, Error of Measurement, Item Sampling, Matrices
Shoemaker, David M. – 1972
Investigated empirically through post mortem item-examinee sampling was the feasibility of the jackknife as a procedure for approximating standard errors of estimate in multiple matrix sampling. The parameters estimated were the mean test score, second through fourth central moments of the test score distribution, and the variance of the item…
Descriptors: Error of Measurement, Error Patterns, Item Sampling, Matrices
Shoemaker, David M. – 1972
Investigated empirically through post mortem item-examinee sampling were the relative merits of two alternative procedures for allocating items to subtests in multiple matrix sampling and the feasibility of using the jackknife in approximating standard errors of estimate. The results indicate clearly that a partially balanced incomplete block…
Descriptors: Error of Measurement, Item Sampling, Matrices, Sampling
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Shoemaker, David M. – Journal of Educational Measurement, 1973
Investigated empirically through post mortem item-examinee samplings were the relative merits of two alternative procedures for allocating items to subtests in multiple matrix sampling and the feasibility of using the jackknife in approximating standard errors of estimate. (Editor)
Descriptors: Databases, Error of Measurement, Item Sampling, Research Design
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Jarjoura, David – Psychometrika, 1983
The problem of predicting universe scores for samples of examinees based on their responses to samples of items is treated. The measurement model categorizes items according to the cells of a table of test specifications, and the linear function derived for minimizing error variance in prediction uses responses to these categories. (Author/JKS)
Descriptors: Error of Measurement, Generalizability Theory, Item Sampling, Prediction
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Shoemaker, David M. – Educational and Psychological Measurement, 1972
Descriptors: Difficulty Level, Error of Measurement, Item Sampling, Simulation
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Adams, Raymond J. – Studies in Educational Evaluation, 2005
Test reliability is a concept central to classical test theory and it is commonly stated as a requirement that a test attain a certain level of reliability before it be considered of sufficient quality for practical use. This article discusses the role of reliability in item response theory, and in particular the role of reliability in contexts…
Descriptors: Test Reliability, Error of Measurement, Item Sampling, Item Response Theory
Moy, Mabel L. Y.; Barcikowski, Robert S. – 1973
Using a computer-based Monte Carlo approach to generate item responses, the results of this study indicate that, when item discrimination indices are considered, item-examinee sampling procedures having the same number of observations have different standard errors in estimating both test mean and test variance. With certain types of tests, a…
Descriptors: Error of Measurement, Evaluation Methods, Item Sampling, Monte Carlo Methods
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Lord, Frederic M. – Psychometrika, 1985
Given a loss function, an asymptotic method for optimal test design for a specified target population of examinees is presented. Also, of more practical use, given an existing unidimensional test and target population, a way is presented to find the loss function for which the test is optimal. (NSF)
Descriptors: Error of Measurement, Higher Education, Item Sampling, Latent Trait Theory
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