Abstract
The limitations inherent in group versus case studies appear to lie in a complementary distribution, underscoring the importance of combining both strategies within a single research program. However, this compromise approach requires analytic tools that permit us to combine and evaluate individual and group data in a common format. Maximum likelihood estimation (MLE) belongs to a family of procedures for determining goodness of fit. MLE can be used in conjunction with a linear or nonlinear model of the way that sources of information combine to determine a given behavioral outcome; such models can be used to estimate the distance between two groups, the degree to which an individual case deviates from a given empirically or theoretically defined group profile, and the degree to which one individual case resembles another. We offer a demonstration of how MLE can be used to evaluate group and individual profiles, in a cross-linguistic study of sentence comprehension in nonfluent aphasic speakers of English, Italian, and German. This includes a demonstration in which the MLE models for each language are "lesioned" to simulate several competing accounts of receptive agrammatism.