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Personality and Social Psychology Review, Vol. 10, No. 4, 282-294 (2006)
DOI: 10.1207/s15327957pspr1004_1

Componential Analysis of Interpersonal Perception Data

David A. Kenny

Tessa V. West

Department of Psychology, University of Connecticut

Thomas E. Malloy

Department of Psychology, Rhode Island College

Linda Albright

Department of Psychology, Westfield State College

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.


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