Detecting Differential Person Functioning in Emotional Intelligence
Alsmadi, Yahia M., Alsmadi, Abdalla A., Journal of Instructional Psychology
Differential Item Functioning (DIF) is a widely used term in test development literature. It is very important to analyze test's data for DIF because It is a serious threat to validity. If the same data matrix was transposed, similar analysis can be carried for Differential Person Functioning (DPF). The purpose of this paper is to introduce and encourage the use of DPF analysis in tests of emotional or cognitive intelligence as a diagnostic approach through two examples illustrating the presence of DPF.
Tests and testing play a major role in today's society. Therefore, it is extremely important that test developers and users strive to insure the validity of their tests and instruments for the target population and purposes for which they were designed for. Therefore, many writers, investigators, and researchers have addressed the notion of test\ or item bias.
Many definitions of item bias have been offered. Runder (1978) suggested that a biased item is one that "behaves differently for members of two different culture groups" (p.33). Angoff (1993) explains that "statistically biased" means a tendency for an estimate to deviate in one direction or another from a true value. It means that, whenever systematically inaccurate estimation occurs, bias is there. However, he believes that "there should be an educational and psychological rational for deciding that a statistically biased item is indeed biased" (p. 114). O'Neal (1991) argues that empirical and statistical indices of bias do not necessarily indicate bias as equivalent to unfairness. Unfair advantages of an item could arise in subpopulation (e.g., males & females) when compared to another subpopulation. This unfair advantage will exist if within the subpopulations both have equal standing on the construct\ or trait being measured. This means that irrelevant sources of variation are not distributed similarly for both subpopulations (Cromwell, 2002). In other words, even when an item shows a significant statistical bias, it might be still judged as a fair item depending on the purpose of the test unless a criterion of overall measure is used to control for the compared subpopulations (Angoff, 1993).
To come over this argument, the term Differential item functioning (DIF) was introduced to mean that an item is functioning differentially (i.e., presents a real and clear bias) if showed different statistical properties in different group settings provided that similar ability levels were controlled while comparing all groups.
In DIF analysis, a data matrix resulting usually from different assessment situations consists of many persons or cases (i. e., the column variable) responding to many test items (i.e., the raw variable). For a particular person, his score on each item is assumed to reflect his\her standing point on the scale of the trait measured by that item. In other words, persons' abilities are being rated by items. But, is it possible to draw the same logic for the opposite case if the same typical data matrix was transposed? Can we think of items being rated (agreed upon\ or persons' proportion correct) by persons.
In short, an item shows DIF when it functions differentially between matched subgroups of persons. An item in a mathematical test, for example, functions differentially for two classes a & b if the item is easier for one class than the other when comparing between subgroups of the same ability level (i.e., total test score) from both classes. Such item functioning behavior is referred to as DIF. Similarly, a person may function differently on two groups of items after controlling for an overall measure. Such person functioning behavior is referred to as differential person functioning or DPF (Johanson & Alsmadi 2000; Alsmadi, 1998).
In their study on DPF in Attitude assessment, Johanson & Osborn (2000) presented an example of DPF with positively and negatively phrased item format. …