How do I print the variance of an lm in R without computing from the Standard Error by hand?

Question

Simple question really! I am running lots of linear regressions of y~x and want to obtain the variance for each regression without computing it from hand from the Standard Error output given in the summary.lm command. Just to save a bit of time :-). Any ideas of the command to do this? Or will I have to write a function to do it myself?

m<-lm(Alopecurus.geniculatus~Year)
> summary(m)

Call:
lm(formula = Alopecurus.geniculatus ~ Year)

Residuals:
    Min      1Q  Median      3Q     Max 
-19.374  -8.667  -2.094   9.601  21.832 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)  
(Intercept) 700.3921   302.2936   2.317   0.0275 *
Year         -0.2757     0.1530  -1.802   0.0817 .
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 11.45 on 30 degrees of freedom
  (15 observations deleted due to missingness)
Multiple R-squared: 0.09762,    Adjusted R-squared: 0.06754 
F-statistic: 3.246 on 1 and 30 DF,  p-value: 0.08168 

So I get a Standard Error output and I was hoping to get a Variance output without calculating it by hand...

Answer 1

I'm not sure what you want the variance of.

If you want the residual variance, it's: (summary(m)$sigma)**2.

If you want the variance of your slope, it's: (summary(m)$coefficients[2,2])**2, or vcov(m)[2,2].

Answer 2

vcov(m)

gives the covariance matrix of the coefficients – variances on the diagonal.

Answer 3

if you're referring to the standard errors for the coefficient estimates, the answer is

summary(m)$coef[,2] 

and if you're referring to the estimated residual variance, it's

summary(m)$sigma

Type names( summary(m) ) and names(m) for other information you can access.