Mixture regression models are an important method for uncovering unobserved heterogeneity. A fundamental challenge in their application relates to the identification of the appropriate number of segments to retain from the data. Prior research has provided several simulation studies that compare...

Part I Methodology -- Chapter 1 Empirical Validation of the 10-Times Rule for SEM -- Chapter 2 Missing Values in RGCCA: Algorithms and Comparisons -- Chapter 3 Comparing Local vs Global Clustering with FIMIX-PLS. Application to Marketing -- Chapter 4 Partial Least Squares Structural Equation...

Partial least squares structural equation modeling (PLS-SEM) has become a popular method for estimating path models with latent variables and their relationships. A common goal of PLS-SEM analyses is to identify key success factors and sources of competitive advantage for important target...