adonis model specification
On 29/09/09 17:41 PM, "Christine Griffiths"
<Christine.Griffiths at bristol.ac.uk> wrote:
Dear Jari and Peter Thanks for the help. It works fine now. Glad it was that simple. :-) I have a number of queries: (1) I am a bit skeptical about the output in that if I run variations of the model, with treatment alone or treatment * block, with or without specifying month as strata, then I get the same p-values = 0.004975 for all factors. This is likely to be a foolish misinterpretation of the results or misspecification of the model. Should I be concerned about this?
Christine, You asked for 200 permutations, and the statistic is one (or 201st) of them, and if your statistic is the first one (most extreme), then you get
1/201
[1] 0.004975124 If you ask for 199 permutations, the lowest possible value will be 1/200 which doesn't look quite as foolish. There was a version of adonis, where one was dropped of the number of permutations if people asked for even hundred. In that version you would have got 199 permutations if you asked for 200. However, after discussing with other developers, I decided that is too patronizing: what are we to say that you should use 199 permutations if you say you want to have 200. Cheers, Jari Oksanen
Call:
adonis(formula = dataset.plot.count ~ treatment * month, data =
dataset.plot.env, permutations = 200, method = "morisita", strata =
dataset.plot.env[, "Month"])
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
treatment 2.0000e+00 1.5313e-01 7.6565e-02 1.1603e+01 0.1033 0.004975
**
month 1.0000e+00 1.7446e-01 1.7446e-01 2.6439e+01 0.1177 0.004975
**
treatment:month 2.0000e+00 5.3241e-02 2.6621e-02 4.0342e+00 0.0359 0.004975
**
Residuals 1.6700e+02 1.1020e+00 6.5987e-03 0.7432
Total 1.7200e+02 1.4828e+00 1.0000
---
Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
(2) Is this the correct way to specify the null hypothesis: there is no
difference between treatments over time? Can I account for block variation
as a random effect?
(3) Because I am interested in testing if my blocks are reliable replicates
of each other, ie have a similar species composition to start with. Do I
need to specify this separately as below for time 1? I.e. not including the
temporal pseudoreplication.
m1<-adonis(dataset.plot.count~treatment*block,data=dataset.time1,permutation=2
00,method="morisita")
I am aware that these are not purely R related questions, so if there is
any easily digestible literature describing the technique in depth, I
would greatly appreciate being directed towards it.
Many thanks in advance,
Cheers
Christine
--On 29 September 2009 07:59 -0600 Peter Solymos <solymos at ualberta.ca>
wrote:
re right, you can supply raw data and use the method argument in adonis to define dissimilarity index (which is "bray" by default).