Browsing by Author "Swaminathan, Hariharan"
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Item An assessment of Stout's index of essential unidimensionality(1996) Hattie, John; Krakowski, Krzysztof; Rogers, H. Jane; Swaminathan, HariharanA simulation study was conducted to evaluate the dependability of Stout’s T index of unidimensionality as used in his DIMTEST procedure. DIMTEST was found to dependably provide indications of unidimensionality, to be reasonably robust, and to allow for a practical demarcation between one and many dimensions. The procedure was not affected by the method used to identify the initial subset of unidimensional items. It was, however, found to be sensitive to whether the multidimensional data arose from a compensatory model or a partially compensatory model. DIMTEST failed when the matrix of tetrachoric correlations was non-Gramian and hence is not appropriate in such cases. Index terms: DIMTEST, essential unidimensionality, factor analysis, item response models, Stout’s test of unidimensionality, tetrachoric correlations, unidimensionality.Item Bias and the effect of priors in Bayesian estimation of parameters of item response models(1990) Gifford, Janice A.; Swaminathan, HariharanThe effectiveness of a Bayesian approach to the estimation problem in item response models has been sufficiently documented in recent years. Although research has indicated that Bayesian estimates, in general, are more accurate than joint maximum likelihood (JML) estimates, the effect of choice of priors on the Bayesian estimates is not well known. Moreover, the extent to which the Bayesian estimates are biased in comparison with JML estimates is not known. The effect of priors and the amount of bias in Bayesian estimates is examined in this paper through simulation studies. It is shown that different specifications of prior information have relatively modest effects on the Bayesian estimates. For small samples, it is shown that the Bayesian estimates are less biased than their JML counterparts. Index terms: accuracy, Bayesian estimates, bias, item response models, joint maximum likelihood estimates, priors.Item A comparison of logistic regression and Mantel-Haenszel procedures for detecting differential item functioning(1993) Rogers, H. Jane; Swaminathan, HariharanThe Mantel-Haenszel (MH) procedure is sensitive to only one type of differential item functioning (DIF). It is not designed to detect DIF that has a nonuniform effect across trait levels. By generalizing the model underlying the MH procedure, a more general DIF detection procedure has been developed (Swaminathan & Rogers, 1990). This study compared the performance of this procedure-the logistic regression (LR) procedure-to that of the MH procedure in the detection of uniform and nonuniform DIF in a simulation study which examined the distributional properties of the LR and MH test statistics and the relative power of the two procedures. For both the LR and MH test statistics, the expected distributions were obtained under nearly all conditions. The LR test statistic did not have the expected distribution for very difficult and highly discriminating items. The LR procedure was found to be more powerful than the MH procedure for detecting nonuniform DIF and as powerful in detecting uniform DIF. Index terms: differential item functioning, logistic regression, Mantel-Haenszel statistic, nonuniform DIF, uniform DIF.