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ERIC Number: EJ883970
Record Type: Journal
Publication Date: 2010
Pages: 21
Abstractor: As Provided
Reference Count: 28
ISSN: ISSN-1076-9986
A Bayesian Approach to Ranking and Rater Evaluation: An Application to Grant Reviews
Cao, Jing; Stokes, S. Lynne; Zhang, Song
Journal of Educational and Behavioral Statistics, v35 n2 p194-214 2010
We develop a Bayesian hierarchical model for the analysis of ordinal data from multirater ranking studies. The model for a rater's score includes four latent factors: one is a latent item trait determining the true order of items and the other three are the rater's performance characteristics, including bias, discrimination, and measurement error in the ratings. The proposed approach aims at three goals. First, three Bayesian estimators are introduced to estimate the ranks of items. They all show a substantial improvement over the widely used score sums by using the information on the variable skill of the raters. Second, rater performance can be compared based on rater bias, discrimination, and measurement error. Third, a simulation-based decision-theoretic approach is described to determine the number of raters to employ. A simulation study and an analysis based on a grant review data set are presented. (Contains 2 tables and 7 figures.)
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A