Checking dimensionality in rasch measurement with standardized residual

Wen Chung WANG

Research output: Contribution to conferencePapers

Abstract

Checking model assumptions is extremely important in Rasch measurement as well as item response theory (IRT). Principal component analysis (PCA) is one widely used method to examine the dimensionality. The first objective of this study is to verify whether a fixed-criterion is appropriate for the determination of dimensionality by investigating distributional properties of the first three eigenvalues when PCA is applied to standardized residuals. Multivariate independence procedure is another method to check the dimensionality. Three statistics have been proposed to assess whether a sample correlation matrix comes from a population with an identity matrix. The second objective of this study is to compare the performances of these statistics when checking dimensionality in Rasch measurement.
Original languageEnglish
Publication statusPublished - 2009
Event2009 Annual Meeting of American Educational Research Association: Disciplined Inquiry: Education Research in the Circle of Knowledge - San Diego, United States
Duration: 13 Apr 200917 Apr 2009

Conference

Conference2009 Annual Meeting of American Educational Research Association: Disciplined Inquiry: Education Research in the Circle of Knowledge
Abbreviated titleAERA2009
Country/TerritoryUnited States
CitySan Diego
Period13/04/0917/04/09

Citation

Wang, W.-C. (2009, April). Checking dimensionality in rasch measurement with standardized residual. Paper presented at the Annual Meeting of American Educational Research Association: Disciplined Inquiry: Education Research in the Circle of Knowledge, San Diego, CA.

Fingerprint

Dive into the research topics of 'Checking dimensionality in rasch measurement with standardized residual'. Together they form a unique fingerprint.