Journal article
Application of latent trait models to identifying substantively interesting raters
Educational measurement, issues and practice, Vol.31(3), pp.31-37
2012
DOI: 10.1111/j.1745-3992.2012.00241.x
Abstract
Historically, research focusing on rater characteristics and rating contexts that enable the assignment of accurate ratings and research focusing on statistical indicators of accurate ratings has been conducted by separate communities of researchers. This study demonstrates how existing latent trait modeling procedures can identify groups of raters who may be of substantive interest to those studying the experiential, cognitive, and contextual aspects of ratings. We employ two data sources in our demonstration—simulated data and data from a large-scale state-wide writing assessment. We apply latent trait models to these data to identify examples of rater leniency, centrality, inaccuracy, and differential dimensionality; and we investigate the association between rater training procedures and the manifestation of rater effects in the real data.
Details
- Title: Subtitle
- Application of latent trait models to identifying substantively interesting raters
- Creators
- Edward W. Wolfe - PearsonAaron Mcvay - Pearson
- Resource Type
- Journal article
- Publication Details
- Educational measurement, issues and practice, Vol.31(3), pp.31-37
- DOI
- 10.1111/j.1745-3992.2012.00241.x
- ISSN
- 0731-1745
- eISSN
- 1745-3992
- Number of pages
- 7
- Language
- English
- Date published
- 2012
- Academic Unit
- Psychological and Quantitative Foundations
- Record Identifier
- 9985123695002771
Metrics
1 Record Views