A new structural equation modeling based method for conditional process analysis

In social science research, the analysis of moderation, mediation, and conditional process is an important methodological question that goes beyond multiple regression. Generally speaking, moderation occurs when the relationship between the independent variable (X) and the dependent variable (Y) varies as a function of a third variable (moderator). Mediation occurs when the effect of X on Y is transmitted through an intervening variable (mediator). Conditional process, collectively, refers to models that combine both mediation and moderation processes. These models are important because they allow researchers to understand, describe, and explain complex social phenomenon and human behavior in a more accurate way. Despite their theoretical usefulness, applied researchers always find it difficult to execute the analysis appropriately due to both technical and conceptual reasons. In this study, a new structural equation modeling (SEM) based method for conditional process analysis is proposed. This method has several advantages as compared to the traditional regression-based approach in terms of its flexibility in model specification, efficiency in parameter estimation, and ability in assessing overall model goodness-of-fit. Computationally, a new computer software program, VS, for implementing the proposed method is introduced. Real examples will be given to demonstrate how VS can be used to examine models that involve conditional process.