CLASSI: A classification model for the study of sequential processes and individual differences therein

In psychological research, one often aims at explaining individual differences in S-R profiles, that is, individual differences in the responses (R) with which people react to specific stimuli (S). To this end, researchers often postulate an underlying sequential process, which boils down to the specification of a set of mediating variables (M) and the processes that link these mediating variables to the stimuli and responses under study. Obviously, a crucial task is to chart how the individual differences in the S-R profiles are caused by individual differences in the S-M link and/or by individual differences in the M-R link. In this paper we propose a new model, called CLASSI, which was explicitly designed for this task. In particular, the key principle of CLASSI consists of reducing the S, M, and R nodes of a sequential process to a few mutually exclusive types and inducing an S-M and an M-R person typology from the data, with the S-M person types being characterized in terms of if S type then M type rules and the M-R person types in terms of if M type then R type rules. As such, the S-M and M-R person types and their associated if-then rules represent the important individual differences in the S-M and M-R links of the sequential process under study. An algorithm to fit the CLASSI model is described and evaluated in a simulation study. An application of CLASSI to data from the behavioral domain of anger and sadness is discussed. Finally, we relate CLASSI to other methods and discuss possible extensions.