Instrumental variables can also be used to estimate reciprocal relationships. To create instrumental variables to test and control for endogeneity you should use the sub-option “Single stochastic variation sharing”, under the new menu option “Explore analytic composites and instrumental variables”.Related YouTube video:Test and Control for Endogeneity in WarpPLS- Reciprocal relationships assessment. This link (i.e., iC C) can also be used to control for endogeneity, thus removing the bias when the path coefficient for the link B C is estimated via ordinary least squares regression. The link iC C can be used to test for endogeneity, via its P value and effect size. A more desirable solution to this problem is to create an instrumental variable iC, incorporating only the variation of A that ends up in C and nothing else, and revise the model so that it has the following links: A B, B C and iC C. Adding a link from A to C could be argued as “solving the problem”, but in fact it creates the possibility of a type I error, since the link A C does not exist at the population level.
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