In this paper a new approach to graphical differential item functioning (DIF) is offered. The methodology is based on a sampling-theory approach to expected response functions (Lewis, 1985; Mislevy, Wingersky, & Sheehan, 1994). Essentially error in item calibrations is modeled explicitly, and repeated samples are taken from the posterior distributions of the item parameters. Sampled parameter values are used to estimate the posterior distribution of the difference in item characteristic curves (ICCs)for two groups. A point-wise expectation is taken as an estimate of the true difference between the ICCs, and the sampled-difference functions indicate uncertainty in the estimate. Tbe approach is applied to a set of pretest items, and the results are compared to traditional Mantel-Haenszel DIF statistics. The expected-response-function approach is contrasted with Pashley's (1992) graphical DIF approach.
