Longisectional interaction structure analysis (LISA) is a method for evaluating multivariate observations in a sample of individuals (patients) at two or more than two subsequent times (stages). It combines cross-sectional configural frequency analysis (CFA) for defining interactions between variables at a given stage with longitudinal interaction structure analysis (ISA) in relating variables observed at two subsequent stages, nonparametrically. The interactions are identified locally as types rather than globally as contingencies, where types are defined as (cross-sectional or longitudinal) patterns occurring in more individuals than expected under H0 of no (cross-sectional or longitudinal) interaction. LISA is applied to data sets from a clinical follow-up study and from a longitudinal study within developmental psychology. It is shown to be a useful technique for the interpretation of such data.