Contingency inferences driven by base rates: Valid by sampling

• Main Authors: Florian Kutzner, Tobias Vogel, Peter Freytag, Klaus Fiedler
• Format: Article
• Language: English
• Published: Society for Judgment and Decision Making 2011-04-01
• Series: Judgment and Decision Making
• Subjects: sampling distribution; operant learning; predictions.NAKeywords
• Online Access: http://journal.sjdm.org/11/9727/jdm9727.pdf

Fiedler et al. (2009), reviewed evidence for the utilization of a contingency inference strategy termed pseudocontingencies (PCs). In PCs, the more frequent levels (and, by implication, the less frequent levels) are assumed to be associated. PCs have been obtained using a wide range of task settings and dependent measures. Yet, the readiness with which decision makers rely on PCs is poorly understood. A computer simulation explored two potential sources of subjective validity of PCs. First, PCs are shown to perform above chance level when the task is to infer the sign of moderate to strong population contingencies from a sample of observations. Second, contingency inferences based on PCs and inferences based on cell frequencies are shown to partially agree across samples. Intriguingly, this criterion and convergent validity are by-products of random sampling error, highlighting the inductive nature of contingency inferences.