Correlated, not causally related, variables

PLS is broadly applied in modern business research. This forum is the right place for discussions on the use of PLS in the fields of Marketing, Strategic Management, Information Technology etc.
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nnhartma
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Joined: Mon Jul 13, 2015 11:48 pm
Real name and title: N Hart, Assistant Prof

Correlated, not causally related, variables

Post by nnhartma » Tue Jul 10, 2018 6:36 pm

One of the benefits of CB-SEM is being able to model a relationship between predictors without specifying the direction of effect via doubled-headed arrows. I understand that we do not have this double-headed option in PLS because of assumptions underlying the approach. But many times, we will have predictor variables that are theoretically related to one (e.g. multiple dimensions of climate or job satisfaction) and we would like to recognize this without specifying a direction to the effect. Does SmartPLS account for this shared variance when estimating the model? If not, can we somehow model it or is SmartPLS a flawed analytical approach when we would expect predictor variables to be theoretically related to one another but do not have theoretical justification for modeling the direction of such impact?

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