Two methods of item selection were used to select sets of 40 items from a 50-item verbal analogies test, and the resulting item sets were compared for relative efficiency. The BICAL program was used to select the 40 items having the best mean square fit to the one parameter logistic (Rasch) model. The LOGIST program was used to select the 40 items with the highest discrimination parameter. Selection was based on two independent samples of 2,500 randomly assigned from a group of 5,000. The set of items selected by the three-parameter program was somewhat more difficult than the set selected by the one-parameter program, but 31 items were common to both sets and there were no other significant differences. The relative efficiency of the two sets of items showed no real differences. It was concluded that both programs tended to select the better items from a well developed item pool, but that the LOGIST program required considerably more computer time. (CTM)