Skip to main content
Componential Analysis of Interpersonal Perception Data
Faculty Publications
  • David A. Kenny, University of Connecticut - Tri-Campus
  • Linda Albright, Westfield State College
  • Thomas E Malloy, Rhode Island College
  • Tessa V. West, University of Connecticut - Tri-Campus
Document Type
Department (Manual Entry)
Dept. of Psychology
Date of Original Version
We examine the advantages and disadvantages of 2 types of analyses used in interpersonal perception studies: componential and noncomponential. Componential analysis of interpersonal perception data (Kenny, 1994) partitions a judgment into components and then estimates the variances of and the correlations between these components. A noncomponential analysis uses raw scores to analyze interpersonal perception data. Three different research areas are investigated: consensus of perceptions across social contexts, reciprocity of attraction, and individual differences in self-enhancement. Finally, we consider criticisms of componential analysis. We conclude that interpersonal perception data necessarily have components (e.g., perceiver, target, measure, and their interactions), and that the researcher needs to develop a model that best captures the researcher's questions. [ABSTRACT FROM AUTHOR].
Citation Information
David A. Kenny, Linda Albright, Thomas E Malloy and Tessa V. West. "Componential Analysis of Interpersonal Perception Data" (2006)
Available at: