Inferential processes in the forced compliance situation: A Bayesian analysis

Abstract

The attribution made by an observer ( O) to an actor in the forced compliance situation was regarded as a probability revision process which can be described by a Bayesian inference model. Os' perceptions of the forced compliance situation were analyzed in terms of the input components into the Bayesian model: prior probabilities of the relevant attitudes and the diagnostic values of the behaviors which the actor may choose. In order to test propositions made by attribution theory about such perceptions ( Kelley, 1967; Messick, 1971), Os viewed actors under conditions of Low Inducement (LI) and High Inducement (HI). Before observing the actor's decision, Os estimated the prior probabilities of the relevant attitudes and the conditional probabilities of compliance and refusal given each of the attitudes. After observing the actor's decision, Os estimated the posterior probabilities of the attitudes. As expected, in the LI condition, compared to the HI condition, compliance was seen as less probable and more diagnostic about the actor's attitudes, and the posterior probability of the corresponding attitude was higher. Contrary to expectations, within both conditions, compliance, compared to refusal, was seen as less diagnostic and more probable.