Commonality analysis is a statistical technique used primarily in the context of multiple regression analysis. Its main purpose is to understand the contribution of individual predictors (independent variables) to the explained variance in a dependent variable. Unlike traditional regression analysis, which mainly focuses on overall model fit and the significance of individual predictors, commonality analysis helps to parse out the unique and shared contributions of predictors in explaining the variance in the outcome variable.
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