Pers Soc Psychol Rev. 2006;10(4):282-94. doi: 10.1207/s15327957pspr1004_1.

Componential analysis of interpersonal perception data.

Personality and social psychology review : an official journal of the Society for Personality and Social Psychology, Inc

David A Kenny, Tessa V West, Thomas E Malloy, Linda Albright

PMID: 17201589 DOI: 10.1207/s15327957pspr1004_1

Abstract

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.

MeSH terms

• Humans
• Interpersonal Relations*
• Judgment
• Models, Psychological*
• Psychology / methods
• Psychology / statistics & numerical data
• Social Perception*

Publication Types

• Journal Article