由线性回归中的每个变量解释的结果方差比例

Question

In the example data set found below I want to calculate the proportion of variance in science explained by each independent variable using linear regression model. How could I achieve that in R?

hsb2 <- read.table('http://www.ats.ucla.edu/stat/r/modules/hsb2.csv', header=T, sep=",")

m1<-lm(science ~ math+female+ socst+ read, data =hsb2)

Answer 1

One of the ways is to use anova() function from stats package. It gives you the residual sum of squares explained by each variable and total sum of squares (ie variance)

anova(m1)
 Analysis of Variance Table

 Response: science
           Df Sum Sq Mean Sq  F value    Pr(>F)    
math        1 7760.6  7760.6 151.8810 < 2.2e-16 ***
female      1  233.0   233.0   4.5599  0.033977 *  
socst       1  465.6   465.6   9.1128  0.002878 ** 
read        1 1084.5  1084.5  21.2254 7.363e-06 ***
Residuals 195 9963.8    51.1                       
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Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1