A Description and Demonstration of the Polytomous-DFIT Framework

Raju, van der Linden, & Fleer (1995) proposed an item response theory based, parametric differential item functioning (DIF) and differential test functioning (DTF) procedure known as differential functioning of items and tests (DFIT). According to Raju et al., the DFIT framework can be used with unidimensional and multidimensional data that are scored dichotomously and/or polytomously. This study examined the polytomous-DFIT framework. Factors manipulated in the simulation were: (1) length of test (20 and 40 items), (2) focal group distribution, (3) number of DIF items, (4) direction of DIF, and (5) type of DIF. The findings provided promising results and indicated directions for future research. The polytomous DFIT framework was effective in identifying DTF and DIF for the simulated conditions. The DTF index did not perform as consistently as the DIF index. The findings are similar to those of unidimensional and multidimensional DFIT studies.

[1]  E. Muraki.  A Generalized Partial Credit Model: Application of an EM Algorithm , 1992 .

[2]  Wim J. van der Linden,et al.  IRT-Based Internal Measures of Differential Functioning of Items and Tests , 1995 .

[3]  Stephen B. Dunbar,et al.  Quality Control in the Development and Use of Performance Assessments , 1991 .

[4]  G. Masters.  A rasch model for partial credit scoring , 1982 .

[5]  Seock-Ho Kim,et al.  A Comparison of Lord's χ2 and Raju's Area Measures In Detection of DIF , 1993 .

[6]  Eiji Muraki,et al.  Fitting a Polytomous Item Response Model to Likert-Type Data , 1990 .

[7]  F. Samejima.  Estimation of latent ability using a response pattern of graded scores , 1968 .

[8]  E. Muraki.  A Generalized Partial Credit Model , 1997 .

[9]  Nambury S. Raju,et al.  Development and Demonstration of Multidimensional IRT‐Based Internal Measures of Differential Functioning of ltems and Tests , 1997 .

[10]  D. Andrich.  A rating formulation for ordered response categories , 1978 .

[11]  F. Lord.  Applications of Item Response Theory To Practical Testing Problems , 1980 .

[12]  Dong-Gun Park,et al.  IRT Item Bias Detection Procedures: Issues of Model Misspecification, Robustness, and Parameter Linking , 1988 .

[13]  Fritz Drasgow,et al.  Study of the measurement bias of two standardized psychological tests. , 1987 .

[14]  R. Darrell Bock,et al.  Estimating item parameters and latent ability when responses are scored in two or more nominal categories , 1972 .

[15]  Hua-Hua Chang,et al.  The unique correspondence of the item response function and item category response functions in polytomously scored item response models , 1994 .

[16]  Gregory L. Candell,et al.  An Iterative Procedure for Linking Metrics and Assessing Item Bias in Item Response Theory , 1988 .

[17]  J. Guilford.  Psychometric methods, 2nd ed. , 1954 .

[18]  T. C. Oshima,et al.  Effect of Sample Size, Number of Biased Items, and Magnitude of Bias on a Two-Stage Item Bias Estimation Method , 1992 .

[19]  R. Zwick,et al.  Assessment of Differential Item Functioning for Performance Tasks , 1993 .

[20]  F. Samejima.  A General Model for Free Response Data. , 1972 .