I have a model that I am running via lme4:

m1 <- lmer (Dependent ~ Tmt1 * Tmt2 + (1 | Block / Tmt1))

I am running this model for each of the three years of my experiment in
turn.  Each treatment is a two level factor (treatment and control).  It is
a split plot design (with Treatment 2 embedded within Treatment 1 embedded
within block).

I'm interested in plotting each level of the interaction between the two
treatments (i.e. 4 means), and some measure of error around each of these
treatment means, for each year in turn.  This first set of models are
Gaussian, but I have another set which use a binomial error distribution.

I am wondering if there is any package available that calculates
interaction treatment means and their error bars for such models?
 Everything I come across completely ignores the random effect variation in
error bar calculation (e.g.the effects package)...

I tried plotLMER.fnc in language R which was useful for my Gaussian model,
but doesn't work for the Binomial one (as the error calculations are based
on an mcmc simulation).  Further I cannot actually extract the HPD 95% CI
values for each treatment that plotLMER gives me!

Using the ez package I have been able to predict the treatment means and
calculate the variance for these means, but I am unsure how to convert
these variances to appropriate error estimations by hand (as I am assuming
I need to take account of the random effect variance too?).  Again this is
only for the Gaussian models...

If anyone has any suggestions it would be much appreciated!  Sorry if this
is a simple question - I am new to these models :-)

Thanks in advance,

Sarah

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