Rafter,

The permutation test goes nowhere near the coefficients. IIRC it works on
the sum of squares decomposition directly.

Jari has already passed on more info about the bootstrapping idea.
Basically the boot package has functions that will apply your function to
bootstrap samples of the original data. Your function, which you need to
write will be a wrapper to adonis() to fit the model to the bootstrap
sample and extract the coefficients you want. boot takes this output and
computes the relevant bootstrap statistics, one of which can be the
standard error.

You'll need to study the boot package to work out how best to write your
wrapper. As the coefficients in the adonis() object are a matrix, not a
single value, you may need to think through how best to fit this into what
boot needs. For example you might extract a single row from the coefficient
matrix thus focussing on a selected variable for all species, and do
separate boot() calls for each of the variables. But I'm thinking about
this from memory so don't take this as gospel; do your homework on boot
well.

HTH

G


On 9 May 2014 11:29, Rafter <liberationecology@gmail.com> wrote:

> Hi Jari,
>
> Thanks so much for your clarification and expansion of Gavin's comments.
>
> I was confused by the application of bootstrapping to a function that is
> already
> using a permutation procedure, but I see now that bootstrapping the
> regression
> coefficients would operate independently of adonis' permutation tests.
>
> I'll try and apply better standards for clarity in the future before
> deciding I
> don't understand something. ;)
>
> Warmly,
> Rafter
>
>
>
>
> --
> View this message in context:
> http://r-sig-ecology.471788.n2.nabble.com/calculating-standard-error-of-coefficients-from-adonis-model-tp7578878p7578887.html
> Sent from the r-sig-ecology mailing list archive at Nabble.com.
>
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-- 

Gavin Simpson, PhD

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