Cues, Components, and Causal Structure in Laboratory Judgment Studies

Abstract

Laboratory studies of judgment in both SCPL and MCPL paradigms generally ignore the issue of the causal structure underlying the correlations between the cue(s) and the distal variable. The present note argues that two possible causal structures must be considered: cue-type tasks, in which the stimuli reflect the value of the distal variable, and component-type tasks, in which the stimuli values cause the distal variable value. It is shown that different optimal response strategies can be derived for a given set of cue validities, depending on which causality assumptions are made, and these optimal strategies are derived for the simple cases for n = 1, 2, and 3. Some implications of these results for the design and interpretation of laboratory studies are suggested.