ERIC Number: EJ722619
Record Type: Journal
Publication Date: 2005
Reference Count: N/A
Further Empirical Results on Parametric Versus Non-Parametric IRT Modeling of Likert-Type Personality Data
Multivariate Behavioral Research, v40 n2 p261-279 2005
Chernyshenko, Stark, Chan, Drasgow, and Williams (2001) investigated the fit of Samejima's logistic graded model and Levine's non-parametric MFS model to the scales of two personality questionnaires and found that the graded model did not fit well. We attribute the poor fit of the graded model to small amounts of multidimensionality present in their data. To verify this conjecture, we compare the fit of these models to the Social Problem Solving Inventory-Revised, whose scales were designed to be unidimensional. A calibration and a cross-validation sample of new observations were used. We also included the following parametric models in the comparison: Bock's nominal model, Masters' partial credit model, and Thissen and Steinberg's extension of the latter. All models were estimated using full information maximum likelihood. We also included in the comparison a normal ogive model version of Samejima's model estimated using limited information estimation. We found that for all scales Samejima's model outperformed all other parametric IRT models in both samples, regardless of the estimation method employed. The non-parametric model outperformed all parametric models in the calibration sample. However, the graded model outperformed MFS in the cross-validation sample in some of the scales. We advocate employing the graded model estimated using limited information methods in modeling Likert-type data, as these methods are more versatile than full information methods to capture the multidimensionality that is generally present in personality data.
Descriptors: Models, Social Problems, Problem Solving, Personality Traits, Personality Measures, Item Response Theory, Nonparametric Statistics, Goodness of Fit, Multidimensional Scaling
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Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
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