[R-sig-ME] Confidence intervals

[Ben Bolker]

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On 14-09-10 07:26 AM, Maik Theelen wrote:
> Dear Ben Bolker,
> 
> I am trying to calculate CI’s for the fixed effects in a lmer
> model.

  Relatively simple questions should *very* preferably be sent to the
r-sig-mixed-models mailing list (cc'd here), please ...

> I am now using the following code
> 
> FUN <- function(fit) { return(fixef(fit)) }
> 
> result <- bootMer(Model, FUN, nsim = 5000)
> 
> bCI.1 <- boot.ci(result, index=1, type="perc") bCI.2 <-
> boot.ci(result, index=1, type="perc") bCI.3 <- boot.ci(result,
> index=1, type="perc") bCI.4 <- boot.ci(result, index=1,
> type="perc")
> 
> Would this be a correct way?

  Are you sure you want index=1 in each case?  Maybe you want
index={1,2,3,4}?

  5000 sims seems like overkill unless your model is very unstable

> 
> When I use *confint* I get the following warning:
> 
> In norm.inter(t, alpha) : extreme order statistics used as
> endpoints

  I don't know exactly why this warning occurs -- you would probably
need to dig in a little bit more and/or read Davison & Hinkley's book
on which the boot package is based? (based on brief googling, it seems
as though your distributions may be badly behaved/need *more*
bootstrap samples).  Plotting the bootstrap distribution, as shown in
example("bootMer"), might be a good idea.


> 
> I would highly appreciate it if you would find the time to answer
> my question.
> 
> Kind Regards,
> 
> Maik Theelen



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