Submitted by Cliff Donath on Sun, 07/10/2011 - 07:30
| Title | A comparison of item selection rules at the early stages of computerized adaptive testing |
| Publication Type | Journal Article |
| Year of Publication | 2000 |
| Authors | Chen, S-Y, Ankenmann, RD, Chang, H-H |
| Journal | Applied Psychological Measurement |
| Volume | 24 |
| Number | 3 |
| Pagination | 241-255 |
| Publication Language | eng |
| Keywords | Adaptive Testing, Computer Assisted Testing, Item Analysis (Test), Statistical Estimation computerized adaptive testing |
| Abstract | The effects of 5 item selection rules--Fisher information (FI), Fisher interval information (FII), Fisher information with a posterior distribution (FIP), Kullback-Leibler information (KL), and Kullback-Leibler information with a posterior distribution (KLP)--were compared with respect to the efficiency and precision of trait (θ) estimation at the early stages of computerized adaptive testing (CAT). FII, FIP, KL, and KLP performed marginally better than FI at the early stages of CAT for θ=-3 and -2. For tests longer than 10 items, there appeared to be no precision advantage for any of the selection rules. (PsycINFO Database Record (c) 2005 APA ) (journal abstract) |