A new item parameter replication method is proposed for assessing the statistical significance of the noncompensatory differential item functioning (NCDIF) index associated with the differential functioning of items and tests framework. In this new method, a cutoff score for each item is determined by obtaining a (1-alpha ) percentile rank score from a frequency distribution of NCDIF values under the no-DIF condition by generating a large number of item parameters based on the item parameter estimates and their variance-covariance structures from a computer program such as BIILOG-MG3. This cutoff for each item can be used as the basis for determining whether a given NCDIF index is significantly different from zero. This new method has definite advantages over the current method and yields cutoff values that are tailored to a particular data set and a particular item. A Monte Carlo assessment of this new method is presented and discussed.