A Bayesian Model for Accuracy and Mutuality in Interpersonal Perception

• Activity Number: 215
• Type: Contributed
• Date/Time: Tuesday, August 13, 2002 : 12:00 PM to 1:50 PM
• Sponsor: Section on Bayesian Stat. Sciences*
• Author(s): Paramjit Gill*+
• Affiliation(s): Okanagan University College
• Keywords: Bayesian analysis ; interpersonal perception ; Markov chain Monte Carlo ; social relations model ; target accuracy ; WinBUGS

Abstract

Accuracy in interpersonal perception is a fundamental topic in social and personal psychology. Are people's perceptions of others valid? This is the most obvious question in the field of interpersonal perception, yet, surprisingly, the most difficult to study. In the 1940-1950s, the study of individual differences in the accuracy of social perception was a dominant area of research. Cronbach (1955) and others argued that a comprehensive understanding of accuracy required more sophisticated procedures than those available at that time. We propose a fully Bayesian approach to the analysis of accuracy in interpersonal perceptions. The Bayesian approach is based on social relations model (SRM) formulation of Kenny (1994). The SRM partitions a response into various "effects" in an additive fashion. Accuracy and mutuality of perceptions is then measured by the interrelationships between these effects.

Computations are carried out using Markov chain Monte Carlo (MCMC) methods as implemented in the software package WinBUGS. We use data from Curry & Emerson (1970), who conducted a longitudinal study on mutual attraction among previously unacquainted students who lived in a residence-hall.