Analyzing Dyadic Data With Multilevel Modeling Versus Structural Equation Modeling: A Tale of Two Methods

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Abstract

Multilevel modeling (MLM) and structural equation modeling (SEM) are the dominant methods for the analysis of dyadic data. Both methods are extensively reviewed for the widely used actor–partner interdependence model and the dyadic growth curve model, as well as other less frequently adopted models, including the common fate model and the mutual influence model. For each method, we discuss the analysis of distinguishable and indistinguishable members, the treatment of missing data, the standardization of effects, and tests of mediation. Even though there has been some blending of the 2 methods, each method has its own advantages and disadvantages, thus both should be in the toolbox of dyadic researchers.

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