A multidimensional model of differential item functioning (DIF) developed by Shealy and Stout is presented. It explains how individual items combine to produce differential test functioning (DTF) at the test level. Recent developments based on this approach, including development of the DIF/DTF detection procedure SIBTEST, are surveyed. The Shealy-Stout model not only offers insight into how DIF can occur, but suggests methods for investigating the root causes of DIF, which are useful to both substantive and statistical researchers of DIF. This new modeling paradigm offers the possibility of the proactive reduction of DIF in tests at the item manufacturing stage. SIBTEST is a nonparametric procedure that both tests for and estimates the amount of DIF in an item or set of items while controlling inflated Type I error by using a regression correction technique. It is shown to perform as well as and in many realistic situations better than other popular DIF assessment procedures. Recent modifications to the procedure demonstrate that it can be an effective tool for examining both crossing DIF and, through the use of kernel smoothing, local DIF. The procedure has been extended for use with tests containing polytomous items as well as tests that are intentionally multidimensional. Many real and simulated data analyses are presented.