Multicollinearity and missing constraints: A comparison of three approaches for the analysis of latent nonlinear effects.

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A Nonlinear Structural Equation Mixture Modeling Approach for Nonnormally Distributed Latent Predictor Variables (2014, background): “For example, the omission of the specification of some measurement error covariances in product indicator approaches can lead to wrong inferences because of underestimated and overestimated effects (Kelava et al., 2008).”
An Evaluation of PLS Based Complex Models: the Roles of Power Analysis, Predictive Relevance and GoF Index (2011, unknown): “In contrast to ML (maximum likelihood) approaches, PLS path modeling is able to estimate large number of latent variables and indicators with a small sample size (Jöreskog and Yang 1996; Kelava et al. 2008; Klein and Moosbrugger 2000; Moosbrugger et al. 2009).”
Mediator and moderator effects of demands on self-control in the relationship between work load and indicators of job strain (2009, result): “…and service work in a large civil administration, both theoretical assumptions were tested with inter alia techniques of SEM that have been statistically proven to provide more valid and reliable results in comparison to traditional approaches to analysis (Cheung & Lau, 2008; Kelava et al., 2008).”