Differential Item Functioning Analysis Using a Mixture 3-Parameter Logistic Model With a Covariate on the TIMSS 2007 Mathematics Test

The purpose of this study was to explore what may be contributing to differences in performance in mathematics on the Trends in International Mathematics and Science Study 2007. This was done by using a mixture item response theory modeling approach to first detect latent classes in the data and then to examine differences in performance on items taken by examinees in the different latent classes. An exploratory mixture 3-Parameter Logistic model analysis detected two latent groups in the data. The model considered in this study used internet access as a covariate to illustrate the effect of the covariate on latent class membership.

[1]  H. van der Flier,et al.  Collateral information and Mixed Rasch models , 1999 .

[2]  Allan S. Cohen,et al.  A Mixture Model Analysis of Differential Item Functioning , 2005 .

[3]  William Stout,et al.  A Multidimensionality-Based DIF Analysis Paradigm , 1996 .

[4]  Allan S. Cohen,et al.  Model Selection Methods for Mixture Dichotomous IRT Models , 2009 .

[5]  H. Wainer,et al.  Differential Item Functioning. , 1994 .

[6]  Brian W. Junker,et al.  Applications and Extensions of MCMC in IRT: Multiple Item Types, Missing Data, and Rated Responses , 1999 .

[7]  Melissa S. Yale,et al.  Differential Item Functioning , 2014 .

[8]  Alka Arora,et al.  TIMSS 2011 User Guide for the International Database. , 2013 .

[9]  Howard Wainer,et al.  Detection of differential item functioning using the parameters of item response models. , 1993 .

[10]  Christine Y. O'Sullivan,et al.  TIMSS 2007 Assessment Frameworks. , 2005 .

[11]  Allan S. Cohen,et al.  Markov chain Monte Carlo estimation of a mixture item response theory model , 2013 .

[12]  Andrew Thomas,et al.  WinBUGS - A Bayesian modelling framework: Concepts, structure, and extensibility , 2000, Stat. Comput..

[13]  María Ester Aguerri,et al.  Detection of Differential Item Functioning , 2012 .

[14]  Terry A. Ackerman A Didactic Explanation of Item Bias, Item Impact, and Item Validity from a Multidimensional Perspective , 1992 .

[15]  Jürgen Rost,et al.  Rasch Models in Latent Classes: An Integration of Two Approaches to Item Analysis , 1990 .

[16]  Richard J. Patz,et al.  A Straightforward Approach to Markov Chain Monte Carlo Methods for Item Response Models , 1999 .

[17]  W. H. Angoff,et al.  Perspectives on differential item functioning methodology. , 1993 .

[18]  Howard Wainer,et al.  Use of item response theory in the study of group differences in trace lines. , 1988 .