I have performed LRT:

> (lL1 <- logLik(mixedModel))

'log Lik.' -65435.99 (df=4)
> (lL2 <- logLik(linearModel<-lm(y~x)))

'log Lik.' -78234.86 (df=3)
> ((Delta <- as.numeric(lL2-lL1)))

[1] -12798.86
> pchisq(- 2 * Delta, 1, lower.tail = FALSE)

[1] 0

How can I understand that 0 from chi-square? Are random effects are statistically important?


1 Answer 1


First, your Delta is negative - a clue that you did something wrong!

Your mixed model has 4 df and the linear one has 3, suggesting it is appropriate to subtract the other direction, yielding a positive difference. However, I don't know what your mixed model is. It is only right if your linear model is nested in the the mixed model.

  • $\begingroup$ linear model is nested in mixed, difference between them is only random effect $\endgroup$
    – user46703
    Commented Aug 23, 2014 at 19:24

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