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How can a regression be significant yet all predictors be non-significant?
X and Y are not correlated (-.01); however, when I place X in a multiple regression predicting Y, alongside three other (related) variables, X and two other variables are significant predictors of Y. Note that the two other variables are significantly correlated with Y.
How should I interpret these findings? X predicts unique variance in Y, but since these are not correlated, it is somehow difficult to interpret.
I know of opposite cases (i.e., two variables are correlated but regression is not significant) and those are relatively simpler to understand from a theoretical and statistical perspective.
