Using a Monte Carlo experimental design, this research examined the relationship between answer patterns' aberrance rates and person-fit statistics (PFS) accuracy. It was observed that as the aberrance rate increased, the detection rates of PFS also increased until, in some situations, a peak was reached and then the detection rates of PFS decreased with increases in aberrance rates. Furthermore, the results suggest that "ECI2[subscript Z]" was somewhat more robust to high levels of aberrance than "l[subscript z]," "H[superscript T]," and "U3" when "cheating" was simulated. The results of this study shed light on a limitation of PFS analysis. (Contains 1 note and 8 figures.)