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I have variables A and B and a target variable Y. Independently, A and not correlated to Y (the P value is too high) and B is correlated to Y with statistical significance. When I put A and B in a multivariate regression model to predict Y, A became significant and B stayed significant. Can someone explain the intuition behind why this happened? Is this why a lot of people say not to pay attention to the p value of a variable when it's in a multivariable regression (heard it from a professor)?

Helene
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    In essence, look also at the relationship between your predictors. A scatter plot matrix should help. – Nick Cox Jan 25 '17 at 12:11
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    Picky point: a multivariate regression is, strict sense, one with two or more response variables. Multivariate and multivariable aren't synonyms. – Nick Cox Jan 25 '17 at 12:13

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