Two frequently used parametric statistics of person-fit with the dichotomous Rasch model (RM) are adjusted and compared to each other and to their original counterparts in terms of power to detect aberrant response patterns in short tests (10, 20, and 30 items). Specifically, the cube root transformation of the mean square for the unweighted person-fit statistic, t, and the standardized likelihood-based person-fit statistic Z3 were adjusted by estimating the probability for correct item response through the use of symmetric functions in the dichotomous Rasch model. The results for simulated unidimensional Rasch data indicate that t and Z3 are consistently, yet not greatly, outperformed by their adjusted counterparts, denoted t* and Z3*, respectively. The four parametric statistics, t, Z3, t*, and Z3*, were also compared to a non-parametric statistic, HT, identified in recent research as outperforming numerous parametric and non-parametric person-fit statistics. The results show that HT substantially outperforms t, Z3, t*, and Z3* in detecting aberrant response patterns for 20-item and 30-item tests, but not for very short tests of 10 items. The detection power of t, Z3, t*, and Z3*, and HT at two specific levels of Type I error, .10 and .05 (i.e., up to 10% and 5% false alarm rate, respectively), is also reported.