[R] likelihood ratio test for mean difference assuming unequal variance
Ben Bolker
bbolker at gmail.com
Tue Jan 14 03:34:31 CET 2014
Amanda Li <amandali <at> uchicago.edu> writes:
>
> Hello,
>
> I am so sorry, but I have been struggling with
> the code for the entire day.
>
> I have a very simple dataset that looks like this:
> response=c(45,47,24,35,47,56,29)
> sub=c("A","A","B","B","C","C","C"£©
> time=c(1,2,1,2,1,2,3)
> gdata=cbind(response,sub,time)
>
> Namely, for three subjects, each has 2 or 3 observations.
> Assuming that each subject has a different
> variance, I want to test whether
> the mean for the three subjects are equal.
>
> I tried:
> library(nlme)
> weight <- varIdent(form = ~ 1 | sub )
> lme1 <- lme(response~sub, weights = weight, data = gdata)
>
> However, it shows error:
> Error in getGroups.data.frame(dataMix, groups) :
> invalid formula for groups
>
> Can anyone help me? Eventually want to try this:
> lme1 <- lme(response~sub, weights = weight, data = gdata)
> lme2 <- lme(response~1, weights = weight, data = gdata)
> lrtest(lme1,lme2)
>
> Am I on the right track? Or can anyone think of a better method?
>
> Thank you very much!
>
> Best regards,
> Amanda
A variety of issues:
(1) you should use data.frame() rather than cbind() to combine
your data: cbind() makes it into a matrix, which converts everything
to character vectors. (2) you should use gls() rather than nlme() --
you don't have a random effect. (3) I really hope this is a toy
example and that your real data are larger, because estimating
means and variance for three groups from 7 data points is
*extremely* optimistic. (If you look at intervals(lme1) you'll
see that the confidence intervals are very wide ...) (4) I'm guessing
lrtest() is from the lmtest package, but you didn't tell us that ...
Ben Bolker
More information about the R-help
mailing list