Advanced Mediating Effects Tests, Multi-Group Analyses, and Measurement Model Assessments in PLS-Based SEM

By Ned Kock. Int. J. e Collab., 2014

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A Note on How to Conduct a Factor-Based PLS-SEM Analysis (2015, methodology): “Reliance on them leads to biased model parameter estimates (notably path coefficients and loadings) even as sample sizes grow to infinity (Kock, 2014b).”
Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods (2018, methodology): “By convention, effect sizes of 0.02, 0.15 and 0.35 are, respectively, termed small, medium and large (Cohen, 1992; Kock, 2014b).”
Empathetic Leadership: How Leader Emotional Support and Understanding Influences Follower Performance (2018, methodology): “Since a PLS-SEM analysis also yields indicator weights, which are proportional to loadings but of lower magnitude, we can augment these convergent validity criteria by also requiring that the P values associated with the weights are equal to or lower than .05 (Kock, 2014, 2015b).”
The assessment of the performance of covariance-based structural equation modeling and partial least square path modeling (2017, methodology): “SEM has been heralded as a unified model that joins methods from econometrics, psychometrics, sociometrics, and multivariate statistics (Bentler, 1994), whereas VB-SEM is an alternative technique to replace the traditional SEM (Lohmöller, 1989; Hair et al., 2011; Kock, 2014).”
Big data analytics capability in supply chain agility (2019, unknown): “Figure 2 presents the estimates obtained via PLS SEM analysis.”