# Percent of variation explained by individual covariates

I understand total variance and R squared in linear regression outputs, but I have difficulty to understand the percent of variation explained by each covariates in a multiple regression analysis. I have two question. 1. How could I explaine the %var explained by one covariates in multiple regression?. 2. Above all how could implement this in Stata or R?. A paper on Table 4, page 7 of the link below has provided such output. Could anyone explain the 1.3% output of Gas stove? The adjusted R squared for the whole regression is 0.79 and the % variance explained by the covariates is 56.8. What does explain the rest?

http://www3.imperial.ac.uk/portal/pls/portallive/docs/1/7292108.PDF

Thanks

• The use of 3D barcharts in that paper invites skepticism. – Matthew Drury Aug 19 '15 at 22:29

This is my guess as to how one could calculate the individual covariate contribution

You can calculate the total sums of squares (TSS) even without running regression

TSS= 1. Now you run the regression with one variable, then calculate the regression sums of squares (RSS)

RSS1= The contribution from variable 1 towards the explained variance is:

    =RSS1/TSS

1. Then add the second variable and calculate the regression sums of squares (RSS2) Contribution from variable 2 towards the explained variance is: