Multicollinearity: is a matrix scatterplot enough to rule it out? - Cross Validated most recent 30 from stats.stackexchange.com 2019-09-18T15:48:07Z https://stats.stackexchange.com/feeds/question/53231 https://creativecommons.org/licenses/by-sa/4.0/rdf https://stats.stackexchange.com/q/53231 0 Multicollinearity: is a matrix scatterplot enough to rule it out? Gaia https://stats.stackexchange.com/users/21238 2013-03-25T12:56:10Z 2013-03-25T12:56:10Z <p>I am analyzing an environmental data set containing one response variable (R) and many explanatory variables.</p> <p>The explanatory variables are either factors (F1, F2, F3) or continuous variables (V1, V2, V3…).</p> <p>I wanted to conduct a linear regression in the form lm (R~F1+F2+F3+V1+V2+V3+F1*F2+F2*F3…)</p> <p>The matrix scatterplot did not show any collinearity issue between my explanatory variable, but from previous analysis (ANOVA) I know that the factors are significantly explaining variation in the continuous variables. (i.e. aov (V1~(F1+F2+F3)^3), all factors significant; (V2~(F1+F2+F3)^3), all factors significant….)</p> <p>The vif in the linear regression model for each explanatory variable is &lt;3.</p> <p>So my questions are:</p> <p>1) If an ANOVA analysis points out a relationship between subsets of explanatory variables are these to be considered collinear?</p> <p>2) Should then I remove all the continuous variables from the analysis?</p>