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PubMed · 17201589

Componential analysis of interpersonal perception data.

David A Kenny·Tessa V West·Thomas E Malloy·Linda Albright
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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.

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HumansInterpersonal RelationsJudgmentModels, PsychologicalPsychologySocial PerceptionJournal Article

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David A Kenny, Tessa V West, Thomas E Malloy, Linda Albright. 2006. Componential analysis of interpersonal perception data.. https://doi.org/10.1207/s15327957pspr1004_1

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