adonis and temporal changes
Valerie, If I understand your design correctly, you're doing a repeated measures analysis, in which isolation is a between-subjects (I.e., between-sites) effect. Year and the year x isolation interaction are within-subjects effects. Because repeated measurements on composition are being taken on the same site in three years, you use strata to restrict the permutation within each site as if site were were a random block containing the different years of measurement. Accordingly, there should be two error terms: site(isolation) to test the isolation main effect, and the site*year(isolation), which in this case is equivalent to the residual error, which is the appropriate error term for testing the year effect and the year x isolation interaction. The test for isolation is wrong because adonis cannot use more than one error term to test effect and thus is using the residual error to test all effects. It should use the site(isolation) term to test the isolation effect, but it does not. Using the residual error to test the isolation effect amounts to pseudoreplication. It assumes that the three measurements of composition in different years on the same site are independent observations. They are not. Often, however, people are not interested in the between-subjects effects (in this case, the main effect of isolation). Rather they are interested in the interaction with time (in this case, isolation x year). I don't see that you are justified in pooling any term with the error term just because it is not significant. Again, the problem is pseudoreplication. You're treating correlated observations as if they were independent observations. Pooling the isolation x year interaction with the residual error term artificially inflates your error df even more. I'm afraid I don't know R well enough to explain how to analyze the covariate. J. Stephen Brewer Professor Department of Biology PO Box 1848 University of Mississippi University, Mississippi 38677-1848 Brewer web page - http://home.olemiss.edu/~jbrewer/ FAX - 662-915-5144 Phone - 662-915-1077
On 2/18/13 1:49 PM, "v_coudrain at voila.fr" <v_coudrain at voila.fr> wrote:
Dear Steve, Thank you very much. I do not exactly understand why the test for isolation will be wrong, would you have some some explanation? In a linear regression, you cannot assess the effect of single variable if the interaction (in which your variable is part) is significant. So if I get a significant result for the isolation*year effect I should conclude that there is an interaction between isolation and year. If the interaction is not significant, should I drop it to get the correct estimate for the year effect? I would have an additional question: I have also an environemental gradient (continuous, one value pro site, constant over the years). Is it possible to include it? Best wishes Valerie
Message du 18/02/13 ? 15h41 De : "Steve Brewer" A : v_coudrain at voila.fr, r-sig-ecology at r-project.org Copie ? : Objet : Re: [R-sig-eco] adonis and temporal changes Valerie, Adonis does not define fixed or random effects, and you therefore cannot define multiple error terms. However, if your model statement looks something like this - isolation*year + site, strata = site - then you will get the correct test for the isolation x year interaction and the correct test for the year effect. The test for isolation will be wrong, because the residual error is used to test all effects, when it is only appropriate for testing the year effect and the year * isolation interaction. The isolation between-subjects effect should be tested with the site effect but is not. The key point is here to make strata = site and to NOT specify the site- interactions with isolation or year. In this way, site will be treated as a block for the within-subjects effects and thus could be considered a random effect. Hope this helps. J. Stephen Brewer Professor Department of Biology PO Box 1848 University of Mississippi University, Mississippi 38677-1848 Brewer web page - http://home.olemiss.edu/~jbrewer/ FAX - 662-915-5144 Phone - 662-915-1077 On 2/18/13 8:19 AM, "v_coudrain at voila.fr" wrote:
Thank you for these explanations. If I put strata=site, this means that for each site my dissimilarity matrix of year 1 and year 2 will be permuted and the observed changes compared to these random permutation? Adding site as a fixed factor then ensure that I am testing changes in time site by site. Am I correct? To my design: I have 30 permanent sites, 10 of each category of isolation (Isolation
=
factor with 3 levels: 3x10 sites = 30 sites). I conducted the samples
in
three years in each site. I have thus 1 sampling (species composition) pro site pro year. I would like to know how the sampled communities change with time, either on a site basis, or at the level of isolation (I may compare multi-site dissimilarity among isolation levels between years). I am not really interested in knowing what proportion of differences in species community is due to space vs time, but I would like to really focus on the temporal changes. That's why I think putting site as a fixed effect should be appropriate. But if you have any suggestion or think this is not
correct,
I would be pleased to have your opinion. Cheers, Valerie On 18/02/2013, at 14:04 PM, Pierre THIRIET wrote:
Dear Val?rie, If I remember well, your design includes: Isolation categories: 3 levels Sites: nested within Isolation categories (10 levels, a total of 30 sites) How many replicates per site and time? Time:? how many years you have? Only one sampling per year? Within sites and years, samples were random or it is always exactly the same area you
sample (e.g. permanent quadrats)?
for adonis, consider that strata is for constraining permutations, which is different than terms in the formulae.
Exactly. The 'strata' only influence the permutations and have no
effect
in formula nor effect defined in the formula. Currently the 'strata' are the only way to constrain the permutations. However, in the R-Forge version of vegan and in vegan 2.2-0 (to be released in April) you can give a permutation matrix as an input to adonis. You can generate
the
permutation matrix with, say, shuffleSet function of the permute
package.
This allows generation of restricted permutations for instance for time series.
Vegan
command vegandocs("permutations") will open up the vignette of the
permute package
for your inspection, and this will give some examples of defining
restricted permutations. At some timeframe we are completely moving to
the permute package,
but you can already use its permutation matrices as input with these
new
and upcoming versions of vegan from R-Forge. Cheers, Jari -- Jari Oksanen, Dept Biology, Univ Oulu, 90014 Finland
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