Applied Psychological Measurement, Volume 17, 1993
Persistent link for this collection
Browse
Browsing Applied Psychological Measurement, Volume 17, 1993 by Author "Baker, Frank B."
Now showing 1 - 3 of 3
Results Per Page
Sort Options
Item Detection of differential item functioning in the graded response model(1993) Cohen, Allan S.; Kim, Seock-Ho; Baker, Frank B.Methods for detecting differential item functioning (DIF) have been proposed primarily for the item response theory dichotomous response model. Three measures of DIF for the dichotomous response model are extended to include Samejima’s graded response model: two measures based on area differences between item true score functions, and a χ² statistic for comparing differences in item parameters. An illustrative example is presented. Index terms: differential item functioning, graded response model, item response theory.Item Equating tests under the nominal response model(1993) Baker, Frank B.Under item response theory, test equating involves finding the coefficients of a linear transformation of the metric of one test to that of another. A procedure for finding these equating coefficients when the items in the two tests are nominally scored was developed. A quadratic loss function based on the differences between response category probabilities in the two tests is employed. The gradients of this loss function needed by the iterative multivariate search procedure used to obtain the equating coefficients were derived for the nominal response case. Examples of both horizontal and vertical equating are provided. The empirical results indicated that tests scored under a nominal response model can be placed on a common metric in both horizontal and vertical equatings. Index terms: characteristic curve, equating, item response theory, nominal response model, quadratic loss function.Item Sensitivity of the linear logistic test model to misspecification of the weight matrix(1993) Baker, Frank B.Under the linear logistic test model, a weight is assigned to each cognitive operation used to respond to an item. The allocation of these weights is open to misspecification that can result in faulty estimates of the basic parameters. The effect on root mean squares (RMSs) of the difference between the parameter estimates obtained under misspecification conditions and those obtained under correct specification conditions was examined. Six levels of misspecification and four sample sizes were used. Even a small number of errors in the weight specifications resulted in large RMS values. However, weight matrices with a high proportion of nonzero elements tended to yield RMSs that were approximately half as large as those with a small number of nonzero elements. Although sample size had some effect on the RMS values, it was quite small compared to that due to the level of misspecification of the weights. The results suggest that because specifying the elements in the weight matrix is a subjective process, it must be done with great care. Index terms: error rates, linear logistic test model, misspecification, parameter estimation, weight matrix.