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Cetin-Berber, Dee Duygu; Sari, Halil Ibrahim; Huggins-Manley, Anne Corinne – Educational and Psychological Measurement, 2019
Routing examinees to modules based on their ability level is a very important aspect in computerized adaptive multistage testing. However, the presence of missing responses may complicate estimation of examinee ability, which may result in misrouting of individuals. Therefore, missing responses should be handled carefully. This study investigated…
Descriptors: Computer Assisted Testing, Adaptive Testing, Error of Measurement, Research Problems
Peer reviewedBan, 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
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
De Ayala, R. J.; And Others – 1991
The robustness of a partial credit (PC) model-based computerized adaptive test's (CAT's) ability estimation to items that did not fit the PC model was investigated. A CAT program was written based on the PC model. The program used maximum likelihood estimation of ability. Item selection was on the basis of information. The simulation terminated…
Descriptors: Adaptive Testing, Computer Assisted Testing, Equations (Mathematics), Error of Measurement
Linacre, John M. – 1990
Advantages and disadvantages of standard Rasch analysis computer programs are discussed. The unconditional maximum likelihood algorithm allows all observations to participate equally in determining the measures and calibrations to be obtained quickly from a data set. On the advantage side, standard Rasch programs can be used immediately, are…
Descriptors: Algorithms, Computer Assisted Testing, Computer Graphics, Computer Simulation
Tatsuoka, Kikumi – 1980
This paper presents a new method for estimating a given latent trait variable by the least-squares approach. The beta weights are obtained recursively with the help of Fourier series and expressed as functions of item parameters of response curves. The values of the latent trait variable estimated by this method and by maximum likelihood method…
Descriptors: Computer Assisted Testing, Error of Measurement, Higher Education, Latent Trait Theory
Patience, Wayne M.; Reckase, Mark D. – 1979
An experiment was performed with computer-generated data to investigate some of the operational characteristics of tailored testing as they are related to various provisions of the computer program and item pool. With respect to the computer program, two characteristics were varied: the size of the step of increase or decrease in item difficulty…
Descriptors: Adaptive Testing, Computer Assisted Testing, Difficulty Level, Error of Measurement
Brown, William L. – 1992
The partial credit model of G. N. Masters (1982), a one-parameter unidimensional polychotomous Rasch model, was used to reduce the error of measurement, particularly for students near the cut score, and to permit measurement to reflect the actual ability of a student more accurately by reducing the degree of misfit for students near the cut…
Descriptors: Ability, Computer Assisted Testing, Cutting Scores, Error of Measurement

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