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Bayesian Logistic Regression: A New Method to Calibrate Pretest Items in Multistage Adaptive Testing
TsungHan Ho – Applied Measurement in Education, 2023
An operational multistage adaptive test (MST) requires the development of a large item bank and the effort to continuously replenish the item bank due to concerns about test security and validity over the long term. New items should be pretested and linked to the item bank before being used operationally. The linking item volume fluctuations in…
Descriptors: Bayesian Statistics, Regression (Statistics), Test Items, Pretesting
Daniel Jurich; Chunyan Liu – Applied Measurement in Education, 2023
Screening items for parameter drift helps protect against serious validity threats and ensure score comparability when equating forms. Although many high-stakes credentialing examinations operate with small sample sizes, few studies have investigated methods to detect drift in small sample equating. This study demonstrates that several newly…
Descriptors: High Stakes Tests, Sample Size, Item Response Theory, Equated Scores