Describes a method of obtaining an average reaction time (RT) distribution for a group of Ss. The method is particularly useful for cases in which data from many Ss are available but there are only 10-20 RT observations per S cell. Essentially, RTs for each S are organized in ascending order, and quantiles are calculated. The quantiles are then averaged over Ss to give group quantiles (Vincent learning curves). From the group quantiles, a group RT distribution can be constructed. It is shown that this method of averaging is exact for certain distributions (i.e., the resulting distribution belongs to the same family as the individual distributions). Furthermore, Monte Carlo studies and application of the method to the combined data from 3 large experiments provide evidence that properties derived from the group RT distribution are much the same as average properties derived from the data of individual Ss. This article also examines how to quantitatively describe the shape of RT distributions. The use of moments and cumulants as sources of information about distribution shape is evaluated and rejected because of extreme dependence on long, outlier reaction times. As an alternative, the use of explicit distribution functions as approximations to RT distributions is considered. (28 ref) (PsycINFO Database Record (c) 2006 APA, all rights reserved). © 1979 American Psychological Association.
