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Wang, Chun; Chen, Ping; Jiang, Shengyu – Grantee Submission, 2019
Many large-scale educational surveys have moved from linear form design to multistage testing (MST) design. One advantage of MST is that it can provide more accurate latent trait [theta] estimates using fewer items than required by linear tests. However, MST generates incomplete response data by design; hence questions remain as to how to…
Descriptors: Adaptive Testing, Test Items, Item Response Theory, Maximum Likelihood Statistics
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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
De Ayala, R. J.; And Others – 1995
Expected a posteriori has a number of advantages over maximum likelihood estimation or maximum a posteriori (MAP) estimation methods. These include ability estimates (thetas) for all response patterns, less regression towards the mean than MAP ability estimates, and a lower average squared error. R. D. Bock and R. J. Mislevy (1982) state that the…
Descriptors: Adaptive Testing, Bayesian Statistics, Error of Measurement, 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
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
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