Tackling measurement problems with Item Response Theory: Principles, characteristics, and assessment, with an illustrative example
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Business Research.
Volume (Year): 57 (2004)
Issue (Month): 2 (February)
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Web page: http://www.elsevier.com/locate/jbusres
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- Eric Bradlow & Howard Wainer & Xiaohui Wang, 1999. "A Bayesian random effects model for testlets," Psychometrika, Springer, vol. 64(2), pages 153-168, June.
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- Salzberger, Thomas & Newton, Fiona J. & Ewing, Michael T., 2014. "Detecting gender item bias and differential manifest response behavior: A Rasch-based solution," Journal of Business Research, Elsevier, vol. 67(4), pages 598-607.
- Silvana Bortolotti & Rafael Tezza & Dalton Andrade & Antonio Bornia & Afonso Sousa Júnior, 2013. "Relevance and advantages of using the item response theory," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(4), pages 2341-2360, June.
- Salzberger, Thomas & Koller, Monika, 2013. "Towards a new paradigm of measurement in marketing," Journal of Business Research, Elsevier, vol. 66(9), pages 1307-1317.
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