This study assesses the accuracy of ASCAL, a microcomputer-based program for estimating item parameters for the three-parameter logistic model in item response theory. Item responses are generated from a three-parameter model, and item parameter estimates from ASCAL are compared to the generating item parameters and to estimates produced by LOGIST. ASCAL, part of an item banking/test construction software package known as MicroCAT, is described as a pseudo-Bayesian estimation process. The program, like LOGIST, is based on a pseudo-maximum likelihood algorithm. Unlike LOGIST, convergence is achieved by postulating prior distributions for examinee ability, item discrimination, and item lower asymptotes. Data are generated for sample sizes of 2,000 and 500, test lengths of 35 and 15, narrow and wide ranges of discrimination, and for centered and decentered ability distributions. The results show that the outputs from the two programs are usually more closely related to each other than either is to the original item parameters. Overall, both programs produce reasonable results for the larger data sets, but both have problems for small sets of data. It is concluded that if both programs are available, LOGIST would still probably be the program of choice due to its greater variety of usage options. (Author/PN)