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John R. Donoghue; Carol Eckerly – Applied Measurement in Education, 2024
Trend scoring constructed response items (i.e. rescoring Time A responses at Time B) gives rise to two-way data that follow a product multinomial distribution rather than the multinomial distribution that is usually assumed. Recent work has shown that the difference in sampling model can have profound negative effects on statistics usually used to…
Descriptors: Scoring, Error of Measurement, Reliability, Scoring Rubrics
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Goodman, Joshua T.; Dallas, Andrew D.; Fan, Fen – Applied Measurement in Education, 2020
Recent research has suggested that re-setting the standard for each administration of a small sample examination, in addition to the high cost, does not adequately maintain similar performance expectations year after year. Small-sample equating methods have shown promise with samples between 20 and 30. For groups that have fewer than 20 students,…
Descriptors: Equated Scores, Sample Size, Sampling, Weighted Scores
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Kopp, Jason P.; Jones, Andrew T. – Applied Measurement in Education, 2020
Traditional psychometric guidelines suggest that at least several hundred respondents are needed to obtain accurate parameter estimates under the Rasch model. However, recent research indicates that Rasch equating results in accurate parameter estimates with sample sizes as small as 25. Item parameter drift under the Rasch model has been…
Descriptors: Item Response Theory, Psychometrics, Sample Size, Sampling
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Kannan, Priya; Sgammato, Adrienne; Tannenbaum, Richard J.; Katz, Irvin R. – Applied Measurement in Education, 2015
The Angoff method requires experts to view every item on the test and make a probability judgment. This can be time consuming when there are large numbers of items on the test. In this study, a G-theory framework was used to determine if a subset of items can be used to make generalizable cut-score recommendations. Angoff ratings (i.e.,…
Descriptors: Reliability, Standard Setting (Scoring), Cutting Scores, Test Items
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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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Michaelides, Michalis P.; Haertel, Edward H. – Applied Measurement in Education, 2014
The standard error of equating quantifies the variability in the estimation of an equating function. Because common items for deriving equated scores are treated as fixed, the only source of variability typically considered arises from the estimation of common-item parameters from responses of samples of examinees. Use of alternative, equally…
Descriptors: Equated Scores, Test Items, Sampling, Statistical Inference
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Phillips, Gary W. – Applied Measurement in Education, 2015
This article proposes that sampling design effects have potentially huge unrecognized impacts on the results reported by large-scale district and state assessments in the United States. When design effects are unrecognized and unaccounted for they lead to underestimating the sampling error in item and test statistics. Underestimating the sampling…
Descriptors: State Programs, Sampling, Research Design, Error of Measurement
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Gao, Xiaohong; And Others – Applied Measurement in Education, 1994
This study provides empirical evidence about the sampling variability and generalizability (reliability) of a statewide performance assessment for grade six. Results for 600 students at individual and school levels indicate that task-sampling variability was the major source of measurement error. Rater-sampling variability was negligible. (SLD)
Descriptors: Achievement Tests, Educational Assessment, Elementary School Students, Error of Measurement