In PLS-SEM, the blindfolding procedure examines the predictive relevance of the model.

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The blindfolding procedure is used to examine the predictive relevance of the model in PLS-SEM. It involves predicting the observed data through a model that is estimated from a subset of the data (e.g., half of the data) and then comparing the predicted values to the observed values in the other subset of the data (e.g., the other half of the data). This helps to assess the stability and generalizability of the model across different samples or subpopulations.

In PLS-SEM, the Blindfolding Procedure Examines the Predictive Relevance of the Model