Using commonality analysis in multiple regressions: a tool to decompose regre…

1. In the face of natural complexities and multicollinearity, model selection and predictions using multiple regression may be ambiguous and risky. Confounding effects of predictors often cloud researchers’ assessment and interpretation of the single best ‘magicmodel’. The shortcomings of stepwise regression have been extensively described in statistical literature, yet it is still widely…