[R-sig-eco] split-split-plot design and adonis

[Steve Brewer]

Edi and Kay,

Assuming one is using Bray-Curtis distances for the species composition
matrix, how are the bc distances among the larger plots (e.g., whole plots
or sites) or the split-plots (site/hydro combos) being calculated here?

I understand that one can use permutation to shuffle the sites as a whole,
but in order to get Sums of Squares for sites to test the sediment effect,
don't you need to be able to calculate distances among sites? How do you
do this if sites are subdivided into hydrologies (and hydrologies
subdivided into depths). You cannot just add up or average the raw
abundances.

Steve

 
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 3/5/12 5:44 AM, "Eduard Szöcs" <szoe8822 at uni-landau.de> wrote:

>Also have a look at the new permute package:
>http://cran.r-project.org/web/packages/permute/index.html
>
>AFAIK permute is not fully hooked up in vegan at the moment (at least
>not in adonis),
>but you could hack the adonis function to use shuffle() instead of
>permuted.index().
>
>The permutation design, as proposed by Kay, would then look like this:
>
>ctrl <- permControl(strata = Site,
>                     within = Within(type = "none"),
>                     blocks = Blocks(type = "free"))
>table(Site, perm.Sediment = Sediment[shuffle(nobs, control = ctrl)])
>
>
>HTH,
>
>Edi
>
>  
>
>
>
>
>On 05/03/12 11:45, Kay Cichini wrote:
>> Hi Arnaud and list-members,
>>
>> what about the following:
>>
>> library(vegan)
>>
>> Sediment<-as.factor(rep(c("Sed1","Sed2","Sed3"),each=36))
>> 
>>Site<-as.factor(rep(c("Site1","Site2","Site3","Site4","Site5","Site6","Si
>>te7","Site8","Site9"),each=12))
>> Hydrology<-as.factor(rep(rep(c("Dry","Wet"),each=6),9))
>> Depth<-as.factor(rep(rep(c("D1","D2"),each=3),18))
>>
>> nobs = length(Site)
>>
>> # depth and hydrology are nested within sites:
>> table(Site, Depth)
>> table(Site, Hydrology)
>>
>> # so the following call is ok as it restricts permutation on sites -
>> # that is, levels of depth and hydrology are shuffled only within and
>>not
>> # across sites:
>> set.seed(123)
>> community<- matrix(rnorm(nobs * 3, 10, 1), nobs, 3)
>> adonis(community ~ Hydrology * Depth, perm = 999, strata = Site)
>>
>> # sediment is different:
>> table(Site, Sediment)
>>
>> # to allow for this structure you would need to shuffle sites as
>> # a whole. the below restriction will randomly assign levels of sediment
>> # to the sites - like this:
>> ctrl = permControl(strata = Site, permute.strata = TRUE)
>> table(Site, perm.Sediment = Sediment[permuted.index2(nobs, control =
>>ctrl)])
>>
>> ### to test sediment you'd need a customized code:
>> (fit<- adonis(community ~ Sediment, permutations = 1))
>>
>> ### number of perms
>> B<- 999
>>
>> ### setting up frame which will be populated by
>> ### random r2 values:
>> pop<- rep(NA, B + 1)
>>
>> ### the first entry will be the true r2:
>> pop[1]<- fit$aov.tab[1, 5]
>>
>> for(i in 2:(B+1)){
>>       idx<- permuted.index2(nobs, control = ctrl)
>>       fit.rand<- adonis(community ~ Sediment[idx], permutations = 1)
>>       pop[i]<- fit.rand$aov.tab[1,5]
>> }
>>
>> ### get the p-value (H0: Sediment has no effect on location of
>>communities):
>> print(pval<- sum(pop>= pop[1]) / (B + 1))
>>
>> ### make a histogram to see random R2-values and the true one:
>> hist(pop, xlab = "Population R2")
>> abline(v = pop[1], col = 2, lty = 3)
>>
>> What do you think?
>> Kay
>>
>>
>> 2012/3/4 Arnaud Foulquier<arnaud.foulquier at gmail.com>
>>
>>> I have run the two analysis. The only differences are the p-values that
>>> appear in the anova tables. Other values (Df, SumsOfSqs, MeanSqs,
>>>F.Model)
>>> are not modified because they are calculated on the "original" (not
>>> permuted) data.
>>>
>>> The p-value is calculated by comparing the value of F obtained with the
>>> original data to the distribution obtained by permutations. If i
>>>understand
>>> well, the strata argument is used to constrain the permutations of the
>>> original data within the groups specified in the strata argument. The
>>> distribution of the F-statistic that is generated by permutations is
>>>not
>>> the
>>> same according to whether the strata argument is specified or not.
>>>This is
>>> why the p-values are modified when the strata argument is specified.
>>>
>>> However, I'm not sure that strata=Site_Hydro correctly specify the
>>>nested
>>> structure of my data.
>>>
>>>
>>>
>>>
>>>
>>> --
>>> View this message in context:
>>> 
>>>http://r-sig-ecology.471788.n2.nabble.com/split-split-plot-design-and-ad
>>>onis-tp7332029p7342690.html
>>> Sent from the r-sig-ecology mailing list archive at Nabble.com.
>>>
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