Using causality assessment indices in PLS-SEM

The article below discusses how one can use causality assessment indices, to assess the network of causal links in a model, in the context of structural equation modeling via partial least squares (PLS-SEM).

Kock, N. (2022). Using causality assessment indices in PLS-SEM. Data Analysis Perspectives Journal, 3(5), 1-6.

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Abstract:

We discuss the use of four causality assessment indices, through an illustrative model analyzed with WarpPLS, a leading software tool for structural equation modeling via partial least squares (PLS-SEM). The indices are the: Simpson's paradox ratio (SPR), R-squared contribution ratio (RSCR), statistical suppression ratio (SSR), and nonlinear bivariate causality direction ratio (NLBCDR). We provide an example of how the causality assessment indices can be presented in a journal article, conference paper, or other research report document.

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