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Incorporating Inter‐item Correlations in Item Response Data Analysis
Author(s) -
Sheng Xiaoming,
Biswas Atanu,
Carrière K.C.
Publication year - 2003
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.200390053
Subject(s) - rasch model , ordinal data , categorical variable , polytomous rasch model , item response theory , ordinal scale , statistics , ordinal regression , latent variable , econometrics , rating scale , mathematics , computer science , psychometrics
This paper concerns with the analysis of item response data, which are usually measured on a rating scale and are therefore ordinal. These study items tended to be highly inter‐correlated. Rasch models, which convert ordinal categorical scales into linear measurements, are widely used in ordinal data analysis. In this paper, we improve the current methodology in order to incorporate inter‐item correlations. We have advocated the latent variable approach for this purpose, in combination with generalized estimating equations to estimate the Rasch model parameters. The data on a study of families of lung cancer patients demonstrate the utility of our methods.