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Castellano, Katherine E.; McCaffrey, Daniel F.; Lockwood, J. R. – Journal of Educational Measurement, 2023
The simple average of student growth scores is often used in accountability systems, but it can be problematic for decision making. When computed using a small/moderate number of students, it can be sensitive to the sample, resulting in inaccurate representations of growth of the students, low year-to-year stability, and inequities for…
Descriptors: Academic Achievement, Accountability, Decision Making, Computation
Sinharay, Sandip – Journal of Educational Measurement, 2016
De la Torre and Deng suggested a resampling-based approach for person-fit assessment (PFA). The approach involves the use of the [math equation unavailable] statistic, a corrected expected a posteriori estimate of the examinee ability, and the Monte Carlo (MC) resampling method. The Type I error rate of the approach was closer to the nominal level…
Descriptors: Sampling, Research Methodology, Error Patterns, Monte Carlo Methods
Albano, Anthony D. – Journal of Educational Measurement, 2015
Research on equating with small samples has shown that methods with stronger assumptions and fewer statistical estimates can lead to decreased error in the estimated equating function. This article introduces a new approach to linear observed-score equating, one which provides flexible control over how form difficulty is assumed versus estimated…
Descriptors: Equated Scores, Sample Size, Sampling, Statistical Inference
Baldwin, Peter – Journal of Educational Measurement, 2011
Growing interest in fully Bayesian item response models begs the question: To what extent can model parameter posterior draws enhance existing practices? One practice that has traditionally relied on model parameter point estimates but may be improved by using posterior draws is the development of a common metric for two independently calibrated…
Descriptors: Item Response Theory, Bayesian Statistics, Computation, Sampling