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1/ Perplexed about multicollinearity in regression models?
Some years ago I wrote a paper, "Where's Waldo: Visualizing Collinearity Diagnostics", introducing novel methods for understanding & visualizing these problems.
⬇️🧵bit.ly/3Ovqzvg
Some years ago I wrote a paper, "Where's Waldo: Visualizing Collinearity Diagnostics", introducing novel methods for understanding & visualizing these problems.
⬇️🧵bit.ly/3Ovqzvg
2/ I've just completed an initial version of the #rstats VisCollin 📦package implementing these methods with a tutorial README at
bit.ly/47yYLyL
bit.ly/47yYLyL
3/ These methods include:
⭐️better tabular presentation of collinearity diagnostics
⭐️a semi-graphic tableplot to make warning and danger levels more salient
⭐️a collinearity biplot of the smallest dimensions of predictor space, where collinearity is most apparent.
⭐️better tabular presentation of collinearity diagnostics
⭐️a semi-graphic tableplot to make warning and danger levels more salient
⭐️a collinearity biplot of the smallest dimensions of predictor space, where collinearity is most apparent.
4/ E.g, this is the tableplot of condition indices & variance decomposition proportions in a model predicting gas mileage from predictors in a dataset of car models.
Interpret: The two PCA dimensions with large condition indices AND 2+ variables with large variance proportions.
Interpret: The two PCA dimensions with large condition indices AND 2+ variables with large variance proportions.
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