The SE is a measure of the models uncertainty about the parameter estimates,
it takes into account your sample size as well as sample variance.  +_2*SE
is usually a good estimate of the 95% confidence interval.  In other words
your treatment effect for treatment2 is probably somewhere between -.6 and
-.86.

On Tue, Sep 15, 2009 at 8:05 PM, Christine Griffiths <
Christine.Griffiths@bristol.ac.uk> wrote:

> I want to plot my predictions from a model and use the standard error
> output as a measure of dispersion as I am unable to calculate confidence
> intervals with mcmcsamp as I have a binomial distribution.
>
> I know that the estimates are deviations from the intercept.
> Fixed effects below:
>                          Estimate Std. Error z value Pr(>|z|)
> (Intercept)                 2.90836    0.34041   8.544  < 2e-16 ***
> treatment2                         -0.73507    0.12986  -5.660 1.51e-08 ***
> treatment3                 -1.20052    0.12371  -9.705  < 2e-16 ***
>
> So the estimate for treatment 2 is 2.9 + -0.73. Are standard errors also
> deviations from the intercept? i.e. 0.34 + 0.13 for treatment 2?
>
> Many thanks
> Christine
>
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>



-- 
Will Morris
Masters of Philosophy candidate
Vesk Plant Ecology Lab
The School of Botany
The University of Melbourne
Australia
Phone: +61 3 8344 0120
http://www.botany.unimelb.edu.au/vesk/

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