Likelihood ratio tests Is likelihood ratio test ($F$-test) of significance of difference of two linear models the same as chi-square test of difference of $-2\log L$?
SAS PROC GLM produces $F$-statistics and PROC MIXED $-2\log L$.
 A: I think that you might be confusing an extra-sum-of-squares F-test with a likelihood ratio test. Although, both are used to compare two models.
A likelihood ratio statistic, denoted by $\Lambda$, is given by 
$$\Lambda = \frac{L\text{(reduced model})}{L(\text{full model})}$$
Taking $-2\log\Lambda$ produces a statistic that has $\chi^2_{d.f(\text{reduced model})-d.f(\text{full model})}$ distribution. That is to say that taking $-2\log$ of the $\Lambda$ gives you a $\chi^2$ distribution. 
I have not used SAS so I cannot comment on the output, but I hope that I have been able to answer your question.
Note: that $\Lambda$ is equivalent to your L

Janne: For linear regression you could use either the likelihood ratio test or the extra-sum-squares F-test and you should end up with the same p-value. Despite, this they are not the same thing. 
As has been mentioned above the likelihood ratio test produces a statistic that has $\chi^2_{d.f(\text{reduced model})-d.f(\text{full model})}$ distribution. Where as an extra-sum-of-squares F-test, given by
$$F = \frac{(SSR_{\text{reduced model}}-SSR_{\text{full model}})/d.f_{\text{reduced model}} - d.f_{\text{full model}}}{\hat{\sigma}^2_\text{full model}}$$
producing a statistic that has $F_{d.f(\text{reduced model})-d.f(\text{full model}),d.f(\text{full model})}$ distribution.
Where SSR is the sum of squared residuals and $\hat{\sigma}^2$ is our standard estimate.
