Dear Prof Kliegl,

Thanks very much for clarifying this issue and providing access to your
illuminating manuscript. I have three brief questions:

1) Figure 4 in your manuscript is very similar to the plot produced by the
code in your example. You desribe the bars around the conditional modes as
'95% prediction intervals'. Are these synonymous with the posterior
variances of the postVar attribute, or did you apply some kind of
transformation?

2) Is it appropriate to cite your manuscript? If so, should the citation
include information not on the website (e.g. journal title)?

3) You recently posted a question about sorting the output from ranef() for
a dotplot (13/10/08). Did you ever figure out how to do this? I guess one
could always extract the components, sort them directly and plot them in
another function...

best wishes, Nick


2009/1/14 Reinhold Kliegl <reinhold.kliegl@gmail.com>

> Well, intervals() is a pretty good nlme response, I think, even if it
> was not exactly answering the question. The lme4 equivalent is
> doplot() which produces a so-called "caterpillar plot" of conditional
> means.
>
> For example:
> ?ranef
>
> fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy)
> rr1 <- ranef(fm1, postVar = TRUE)
> dotplot(rr1,scales = list(x = list(relation = 'free')))[["Subject"]]
>
> It is important to be clear about the distinction between random
> effect estimates of variances and correlations, provided as part of
> the model output and the conditional means for groups/units based on
> ("predicted with") them. At least, correlations computed from
> conditional means can differ strongly from the correlation estimates.
> The short story: You should only trust the model estimates. As Greg
> Lee said, conditional means are to be handled with care; you can not
> apply any of the usual inferential statistics to them. Nevertheless,
> the caterpillar plots are highly informative and diagnostic about, for
> example, whether you need a random effect to account for unit-by-unit
> variability. They may also lead you to  discover distinct subgroups
> suggestive of a fixed effect (for a future model). There is a
> manuscript at the top of my publications page for download (and
> constructive feedback) walking through an example.
>
> Reinhold Kliegl
>
>

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