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A Multiple-Perspective Approach to Data Analysis in Congruence Research

Department of Management, The Chinese University of Hong Kong, Shatin, Hong Kong, gordonc{at}cuhk.edu.hk

Despite the popularity of the congruence construct (similarity, fit, and agreement) in organizational theories, the operationalization of congruence and the appropriate methods to analyze it have concerned many researchers. A structural equation modeling-based latent congruence model (LCM) that operationalizes congruence as the mean and difference of the component measures has recently been introduced. The LCM provides a simple analytical framework for examining the measurement equivalence of the component measures and for conducting congruence analysis and component analysis. The objective of this note is to highlight the similarities and differences between the LCM and the polynomial regression (PR) approach to studying congruence. The major difference is that the LCM considers congruence and its components as distinctive constructs, and therefore they can be used to answer different research questions. The determination of which constructs and analytical approach to use should be based on the theory and research hypotheses that answer the research question. Indeed, because LCM provides a simple framework for both congruence analysis and component analysis, researchers are encouraged to answer their research questions from both perspectives.

Key Words: data analysis • latent congruence model • component analysis • polynomial regression

This version was published on January 1, 2009

Organizational Research Methods, Vol. 12, No. 1, 63-68 (2009)
DOI: 10.1177/1094428107310091


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