Hello,

I would like to calculate the R-Squared and p-value (F-Statistics) for my model (with Standard Robust Errors). Can someone explain to me how to get them for the adapted model (modrob)?

The regression without standard robust error:

```
>mod=lm(giniA~region+dummy_2009+age,data=fors)
Call:
lm(formula = giniA ~ region + dummy_2009 + age, data = fors)
Residuals:
Min 1Q Median 3Q Max
-0.13714 -0.01402 0.00192 0.01458 0.09922
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 6.167e-01 1.917e-03 321.749 < 2e-16 ***
regionWest 2.218e-03 1.408e-03 1.575 0.115
dummy_2009 -2.225e-02 1.205e-03 -18.473 < 2e-16 ***
age -1.858e-04 3.858e-05 -4.816 1.6e-06 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.02381 on 1624 degrees of freedom
Multiple R-squared: 0.2034, Adjusted R-squared: 0.202
F-statistic: 138.3 on 3 and 1624 DF, p-value: < 2.2e-16
```

And this is my regression with standard robust errors, for which I would like to calculate the R-squared and p-value(F-statistics):

```
# model with robust standard errors:
> modrob = coeftest(mod,vcov. = vcovHAC)
t test of coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 6.1666e-01 2.0404e-03 302.2289 < 2.2e-16 ***
regionWest 2.2179e-03 1.4474e-03 1.5324 0.1256
dummy_2009 -2.2254e-02 1.1846e-03 -18.7869 < 2.2e-16 ***
age -1.8582e-04 4.2784e-05 -4.3431 1.491e-05 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
```

Thank you very much.