A Multiple-Perspective Approach to Data Analysis in Congruence Research
比较了基于结构方程模型的潜在一致性模型（LCM）与多项式回归方法在研究一致性（相似性、匹配、一致）时的异同，指出LCM将一致性及其组成部分视为不同构念，可回答不同研究问题，并鼓励研究者从两个视角分析数据。
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.