Item-level fit analysis not only serves as a complementary check to global fit analysis, it is also essential in scale development because the fit results will guide item revision and/or deletion (Liu & Maydeu-Olivares, 2014). During data collection, missing response data may likely happen due to various reasons. Chi-square-based item fit…

Research has found that the "a"-stratified item selection strategy (STR) for computerized adaptive tests (CATs) may lead to insufficient use of high a items at later stages of the tests and thus to reduced measurement precision. A refined approach, unequal item selection across strata (USTR), effectively improves test precision over the…

Eight independent variables (differential item functioning [DIF] detection method, purification procedure, item response model, mean latent trait difference between groups, test length, DIF pattern, magnitude of DIF, and percentage of DIF items) were manipulated, and two dependent variables (Type I error and power) were assessed through…

As item response theory (IRT) becomes popular in educational and psychological testing, there is a need of reporting IRT-based effect size measures. In this study, we show how the standardized mean difference can be generalized into such a measure. A disattenuation procedure based on the IRT test reliability is proposed to correct the attenuation…