Uncovering and Treating Unobserved Heterogeneity with FIMIX-PLS: Which Model Selection Criterion Provides an Appropriate Number of Segments?

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Multigroup Analysis in Partial Least Squares (PLS) Path Modeling: Alternative Methods and Empirical Results (2011, methodology): “(2009) applied the FIMIX-PLS method (Hahn et al., 2002; Rigdon et al., 2010; Ringle, Wende, & Will, 2010; Ringle, Sarstedt, & Mooi, 2010; Sarstedt et al., 2011; Sarstedt & Ringle, 2010) to the original study by Festge and Schwaiger (2007) to uncover unobserved heterogeneity.”
Discovering Unobserved Heterogeneity in Structural Equation Models to Avert Validity Threats (2013, methodology): “In mixture models, these heuristics include model-selection criteria that are well known from the model-selection literature (e.g., AIC, BIC, and CAIC) and can also be used to approximate the best fitting number of segments (Andrews and Currim 2003a; Sarstedt et al. 2011a).”
PLS-SEM: Looking Back and Moving Forward (2014, methodology): “…Sarstedt and Ringle, 2010), analysis of interaction effects (Henseler and Chin, 2010; Henseler and Fassott, 2010), nonlinear effects (Dijkstra and Henseler, 2011; Henseler et al., 2012; Rigdon et al., 2010) or multi-group analysis procedures (e.g., Rigdon et al., 2010; Sarstedt et al., 2011b).”