A necessary prerequisite to the operational use of item response theory (IRT) in any testing program is the investigation of the feasibility of such an approach. This report presents the results of such research for the Graduate Management Admission Test (GMAT). Despite the fact that GMAT data appear to violate a basic assumption of the three-parameter logistic item response model, local independence, the model was able to replicate accurately the observed item responses. IRT-based equating was consistent across two randomly selected samples and four selected subpopulations (male, female, younger examinees, and older examinees) and produced converted scores very similar to those produced by the current GMAT equating method--linear section pre-equating--a method that makes different assumptions than those required by IRT. It appears that for GMAT item types and populations, any effect of the violation of local independence on IRT true-score equating is negligible. This research has shown IRT equating to be feasible for the GMAT; but, because the local independence assumption of IRT appears to be violated, further experience is needed before other IRT methods--such as optimal test development using item information, or computerized adaptive testing--could be used for GMAT. (Author)