CODEWITHSUNDEEP
rstatisticsregression
Jake Long
Jake Long

Reputation: 25

How to get each independent variables R^2 in a multivariate linear regression

When you do a multivariate linear regression you get the multiple R-squared, like this: enter image description here

My question is, if I can get the R-squared for each independent variable, without having to make a regression for each of the predictor variables.

For example, is it possible to get the R-squared for each of the predictor variables, next to the p value: enter image description here

Upvotes: 0

Views: 2444

Answers (1)

Martin Wettstein
Martin Wettstein

Reputation: 2904

In regression models, individual variables do not have an R-squared. There is only ever an R-squared for a complete model. The variance explained by any single independent variable in a regression model is depending on the other independent variables.

If you need some added value of an independent variable, that is, the variance this IV explains above all others, you can compute two regression models. One with this IV and one without. The difference in R-squared is the variance this IV explains after all others have explained their share. But if you do this for all variables, the differences won't add up to the total R-squared.

Alternatively, you may use squared Beta weights to roughly estimate the effect size of a variable in a model. But this value is not directly comparable to R-squared.

This said, this question would better be posted in CrossValidated than StackOverflow.

Upvotes: 2

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