The  present  study  aimed  at  investigating  DIF  sources  on  an  EFL  reading  comprehension test.  Accordingly,  2  DIF  detection  methods,  logistic  regression  (LR)  and  item  response theory  (IRT),  were  used  to  flag  emergent  DIF  of  203  (110  females  &  93  males)  Iranian EFL examinees’ performance on a reading comprehension test. Seven hypothetical DIF sources were examin...

Context is a vague notion with numerous building blocks making language test scores inferences quite convoluted. This study has made use of a model of item responding that has striven to theorize the contextual infrastructure of differential item functioning (DIF) research and help specify the sources of DIF. Two steps were taken in this research: first, to identify DIF by gender grouping via l...

The generalizability aspect of Construct validity, as proposed by Messick (1989), requires that a test measures the same trait across different samples from the same population. Differential Item functioning (DIF) analysis is a key component in the fairness evaluation of educational tests. University entrance exam for the candidates who seek admission into master's English programs (MEUEE) at I...

Data and information fusion (DIF) involves a process of combining data from multiple inputs (from one or more sources such as sensors and textual reports).1 The aim is to obtain information that is better (more useful and meaningful) than that would be derived from each of the sources individually (that is, without fusing). DIF is emerging as an important field of multidisciplinary study [113, ...

Abstract In latent scaling applications, such as the positioning of political parties, differential item functioning (DIF) may occur because measurement issues or substantive differences in association between and manifest variables. While first source DIF has received considerable attention, second not, although it is potential interest to comparative scholars. this research note, we introduce...

Differential item functioning (DIF) can lead to an unfair advantage or disadvantage for certain subgroups in educational and psychological testing. Therefore, a variety of statistical methods has been suggested for detecting DIF in the Rasch model. Most of these methods are designed for the comparison of pre-specified focal and reference groups, such as males and females. Latent class approache...

A variety of statistical methods have been suggested for detecting differential item functioning (DIF) in the Rasch model. Most of these methods are designed for the comparison of pre-specified focal and reference groups, such as males and females. Latent class approaches, on the other hand, allow the detection of previously unknown groups exhibiting DIF. However, this approach provides no stra...