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Ban, Jae-Chun; Hanson, Bradley A.; Yi, Qing; Harris, Deborah J. – Journal of Educational Measurement, 2002
Compared three online pretest calibration scaling methods through simulation: (1) marginal maximum likelihood with one expectation maximization (EM) cycle (OEM) method; (2) marginal maximum likelihood with multiple EM cycles (MEM); and (3) M. Stocking's method B. MEM produced the smallest average total error in parameter estimation; OEM yielded…
Descriptors: Computer Assisted Testing, Error of Measurement, Maximum Likelihood Statistics, Online Systems
Ban, Jae-Chun; Hanson, Bradley A.; Wang, Tianyou; Yi, Qing; Harris, Deborah J. – 2000
The purpose of this study was to compare and evaluate five online pretest item calibration/scaling methods in computerized adaptive testing (CAT): (1) the marginal maximum likelihood estimate with one-EM cycle (OEM); (2) the marginal maximum likelihood estimate with multiple EM cycles (MEM); (3) Stocking's Method A (M. Stocking, 1988); (4)…
Descriptors: Adaptive Testing, Comparative Analysis, Computer Assisted Testing, Estimation (Mathematics)
Yi, Qing; Wang, Tianyou; Ban, Jae-Chun – 2000
Error indices (bias, standard error of estimation, and root mean square error) obtained on different scales of measurement under different test termination rules in a computerized adaptive test (CAT) context were examined. Four ability estimation methods were studied: (1) maximum likelihood estimation (MLE); (2) weighted likelihood estimation…
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Error of Measurement
Ban, Jae-Chun; Hanson, Bradley A.; Yi, Qing; Harris, Deborah J. – 2002
The purpose of this study was to compare and evaluate three online pretest item calibration/scaling methods in terms of item parameter recovery when the item responses to the pretest items in the pool would be sparse. The three methods considered were the marginal maximum likelihood estimate with one EM cycle (OEM) method, the marginal maximum…
Descriptors: Adaptive Testing, Computer Assisted Testing, Data Analysis, Error of Measurement