2 resultados para segmental duplication

em DigitalCommons@University of Nebraska - Lincoln


Relevância:

10.00% 10.00%

Publicador:

Resumo:

The complexities involved in obtaining permits for field research using protected species continue to increase. In October 1988, Congress amended the Marine Mammal Protection Act (MMPA) to increase the documentation required to obtain a scientific research permit (PL 100-711). Applicants for scientific research permits must now submit “information indicating that the taking is required to further a bona fide scientific purpose and does not involve unnecessary duplication of research.”

Relevância:

10.00% 10.00%

Publicador:

Resumo:

The 3PL model is a flexible and widely used tool in assessment. However, it suffers from limitations due to its need for large sample sizes. This study introduces and evaluates the efficacy of a new sample size augmentation technique called Duplicate, Erase, and Replace (DupER) Augmentation through a simulation study. Data are augmented using several variations of DupER Augmentation (based on different imputation methodologies, deletion rates, and duplication rates), analyzed in BILOG-MG 3, and results are compared to those obtained from analyzing the raw data. Additional manipulated variables include test length and sample size. Estimates are compared using seven different evaluative criteria. Results are mixed and inconclusive. DupER augmented data tend to result in larger root mean squared errors (RMSEs) and lower correlations between estimates and parameters for both item and ability parameters. However, some DupER variations produce estimates that are much less biased than those obtained from the raw data alone. For one DupER variation, it was found that DupER produced better results for low-ability simulees and worse results for those with high abilities. Findings, limitations, and recommendations for future studies are discussed. Specific recommendations for future studies include the application of Duper Augmentation (1) to empirical data, (2) with additional IRT models, and (3) the analysis of the efficacy of the procedure for different item and ability parameter distributions.