Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 5 of 5 for “"true score equating"”.
-
A comparison of kernel equating and item response theory true score equating
… study compares the accuracy of NEAT-design IRT true score equating (TIRT) and kernel equating (KE) in different conditions. The relative accuracy of three methods (Stocking-Lord transformation based TIRT (SL TIRT), kernel chain equipercentile equating (KE CE) and kernel post-stratification …
-
THE IMPACT OF ANCHOR ITEM EXPOSURE ON MEAN/SIGMA LINKING AND IRT TRUE SCORE EQUATING UNDER THE NEAT DESIGN
To compare examinees' true ability and their actual competence on the content being measured across different test administrations, test scores must be equated. One of the most common equating designs is called the nonequivalent anchor test (NEAT) design. This equating design requires two forms of …
-
The Robustness of Rasch True Score Preequating to Violations of Model Assumptions Under Equivalent and Nonequivalent Populations
… study examined the feasibility of using Rasch true score preequating under violated model assumptions and nonequivalent populations. Dichotomous item responses were simulated using a compensatory two dimensional (2D) three parameter logistic (3PL) Item Response Theory (IRT) model. The Rasch …
-
Effect of Sample Size on Irt Equating of Uni-Dimensional Tests in Common Item Non-Equivalent Group Design: a Monte Carlo Simulation Study
Test equating is important to large-scale testing programs because of the following two reasons: strict test security is a key concern for high-stakes tests and fairness of test equating is important for test takers. The question of adequacy of sample size often arises in test equating. However, …
-
A stepwise test characteristic curve method to detect item parameter drift
… assumption of item response theory (IRT) based equating is that the item parameters should be invariant over different testing occasions. Sometimes, however, item parameters do not remain invariant due to factors other than sampling error, and this is termed item parameter drift (IPD). Several …