ERIC Number: EJ1086572
Record Type: Journal
Publication Date: 2016-Feb
Abstractor: As Provided
Reference Count: 28
It Might Not Make a Big DIF: Improved Differential Test Functioning Statistics That Account for Sampling Variability
Chalmers, R. Philip; Counsell, Alyssa; Flora, David B.
Educational and Psychological Measurement, v76 n1 p114-140 Feb 2016
Differential test functioning, or DTF, occurs when one or more items in a test demonstrate differential item functioning (DIF) and the aggregate of these effects are witnessed at the test level. In many applications, DTF can be more important than DIF when the overall effects of DIF at the test level can be quantified. However, optimal statistical methodology for detecting and understanding DTF has not been developed. This article proposes improved DTF statistics that properly account for sampling variability in item parameter estimates while avoiding the necessity of predicting provisional latent trait estimates to create two-step approximations. The properties of the DTF statistics were examined with two Monte Carlo simulation studies using dichotomous and polytomous IRT models. The simulation results revealed that the improved DTF statistics obtained optimal and consistent statistical properties, such as obtaining consistent Type I error rates. Next, an empirical analysis demonstrated the application of the proposed methodology. Applied settings where the DTF statistics can be beneficial are suggested and future DTF research areas are proposed.
Descriptors: Test Bias, Sampling, Test Items, Statistical Analysis, Monte Carlo Methods, Foreign Countries, Self Concept Measures, Self Efficacy, Error of Measurement, Item Response Theory
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Authoring Institution: N/A
Identifiers - Location: Canada; Germany