A Decision-making Subgraph Mining Algorithm for Structural Equation Modeling

As an advanced method of multivariate data analysis, structural equation modeling (SEM) is to obtain relationships among latent variables in structural models. One characteristic of SEM models is that the same substructures exist in structural models with the same evaluated values. Thus, structural models can be obtained by searching for relationship subgraphs representing substructures. Based on the finding, a decision-making subgraph mining algorithm (DmSMA) is proposed to search for subgraphs which potentially belong to structural models. Experiments of SEM implemented by DmSMA are conducted to indicate that searching for decision-making subgraphs is helpful to obtain effective structural models. As shown by the experimental results including two performance metrics, DmSMA performs better than the compared algorithms to solve SEM through mining decision-making subgraphs.