Yet another new YouTube video is available for WarpPLS:

This video shows how path coefficients sometimes go up, and P values become significant, when warping takes place in a structural equation modeling (SEM) analysis using the software WarpPLS.

Since path coefficients are typically associated with hypotheses, which are supported if the paths are found to be significant, this will likely be music to many researchers' ears.

However, it is important to make two important points regarding this effect:

1. Path coefficients are not artificially inflated. They increase simply because the software is taking the nonlinear associations between latent variables into account when estimating path coefficients. Much like a researcher would apply a log(X) transformation to a predictor, before an ordinary regression analysis, if he or she knew that the predictor's relationship with a criterion variable Y was of the type Y=log(X).

2. Path coefficients do not always increase. Due to the nature of standardized partial regression coefficient calculation (the path coefficients, or betas, are standardized partial regression coefficients), when several predictor latent variables (LVs) point a one criterion LV, if one of the predictor LVs increases, some of the others predictor LVs may decrease as a result. In a sense, the predictor LVs "compete" for pieces of the space of variance explained for the criterion LV; if the predictor LVs are correlated, they tend "steal" variance space from each other (so to speak).

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