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ERIC Number: ED464109
Record Type: Non-Journal
Publication Date: 2002-Apr
Pages: 14
Abstractor: N/A
Reference Count: N/A
Some Features of the Sampling Distribution of the Ability Estimate in Computerized Adaptive Testing According to Two Stopping Rules.
Blais, Jean-Guy; Raiche, Gilles
This paper examines some characteristics of the statistics associated with the sampling distribution of the proficiency level estimate when the Rasch model is used. These characteristics allow the judgment of the meaning to be given to the proficiency level estimate obtained in adaptive testing, and as a consequence, they can illustrate the meaningfulness of the proficiency level estimate. A Monte Carlo method computer-based simulation was used to investigate these characteristics. Findings show that with the Rasch model, and the expected a posteriori estimation method, if the theoretical distribution of the proficiency level is postulated as normal, then the stopping rule according to the number of items administered should be applied only if at least 13 items are administered. In general, it is preferable not to use the stopping rule according to the standard error with a standard error retained above 0.40. The results also suggest the application of the correction developed by R. Bock and R. Mislevy no matter which stopping rule is used, to reduce the bias of the proficiency level estimate over the entire proficiency range. (Contains 2 tables and 24 references.) (SLD)
Publication Type: Reports - Research; Speeches/Meeting Papers
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A