Likelihood ratios
oops, I guess that should be: LR = exp( anova( fit1 , fit2 )$Chisq[2] / -2 )
On Tue, Jun 1, 2010 at 1:28 PM, Mike Lawrence <Mike.Lawrence at dal.ca> wrote:
Hi folks, I have 2 lmer fits, one (fit1) nested in the other (fit2), and I'd like to compute the likelihood ratio comparing the models so I can say something like "there is X times more evidence for fit1 than for fit2" (as in Glover & Dixon, 2004, www.ncbi.nlm.nih.gov/pubmed/15732688). I know I can use anova(fit1,fit2) to obtain a null-hypothesis significance test of the fits, and I suspect the output also contains the information I need to make my evidentiary statement, but I'm not confident of what I'm doing here. Is it correct that the reported value of chi-square from anova() is simply the D of the likelihood ratio test (http://en.wikipedia.org/wiki/Likelihood_ratio_test)? If so, does it sound right that I can simply derive the complexity-corrected likelihood ratio as: LR = exp( -2 * anova( fit1 , fit2 )$Chisq[2] ) ? Mike -- Mike Lawrence Graduate Student Department of Psychology Dalhousie University Looking to arrange a meeting? Check my public calendar: http://tr.im/mikes_public_calendar ~ Certainty is folly... I think. ~
Mike Lawrence Graduate Student Department of Psychology Dalhousie University Looking to arrange a meeting? Check my public calendar: http://tr.im/mikes_public_calendar ~ Certainty is folly... I think. ~