On detecting nonlinear noncompensatory judgment strategies: Comparison of alternative regression models

We compare the performance of the two models that are usually used to detect nonlinear noncompensatory (NLNC) judgment strategies - Einhorn′s (1970) parabolic and hyperbolic models - to two new models: (1) The scatter model (Brannick and Brannick, 1989), which includes, in addition to the linear combination of attribute values, a nonlinear term - the within profile scatter of the attributes; and (2) The “true conjunctive-disjunctive” model (TCD model), which includes additional nonlinear terms associated with the relative values of the attributes. The analyses of 12 empirical datasets indicate that the scatter model is the best NLNC model in terms of model fit. Furthermore, the analyses also indicate that when judgment strategies are relatively homogeneous, the nonlinear terms of the scatter model and the TCD model are most useful measures of NLNC strategies because they are statistically more powerful than model fit-based measures and because they permit the representation of judgment strategies on a conjunctive-disjunctive continuum. The nonlinear term of the scatter model also allows testing for NLNC strategies on the individual level.