Item bias and item response theory

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Abstract

In this chapter the definition, detection, and explanation of item bias is discussed. Item bias is generally defined as conditional dependence; within the framework of item response theory the general definition implies that the item characteristic curves of two groups do not coincide. For detecting biased items, statistical tests and indices based on item response theory have been proposed. Several methods have been compared using empirical or simulated data. Methods combining information on the regression of item responses on latent trait or observed test score and information on the latent trait or observed test score distribution appear to do a good job in detecting biased items. Next to these general methods, specific methods are available that might perform better under specific assumptions and conditions. For explaining detected item bias, four strategies are described: (1) qualitative, (2) correlational, (3) quasi-experimental, and (4) experimental research.

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