[R-sig-eco] repeated measures NMDS?

[Kay Cecil Cichini]

gavin,

sorry - of course it should be permute.strata=F, permuting within 
individual sites!
but despite of this the code should work, doesn't it?

thanks,
kay



Gavin Simpson schrieb:
> On Wed, 2010-11-10 at 23:33 +0100, Kay Cecil Cichini wrote:
>> hi eduard,
>>
>> i faced similar problems recently and came to the below solution.
>> i only try to address the pseudoreplication with an appropiate  
>> permutation scheme.
>> when it comes to testing the interactions, things may get more complicated.
>>
>> the code is in no way approven of, but at least it maybe good enough  
>> for a starter.
>>
>> best,
>> kay
> 
> Hi Kay,
> 
> I don't think you have this right.

> 
> If you have measured repeatedly, say 5 times, on the same 10
> individuals, or if you have ten fields and you take 5 quadrats from
> each, you need to permute *within* the individuals/fields, not permute
> the individuals/fields which is what permute.strata does. permute.strata
> would be useful in evaluating factors that vary at the block
> (individuals/fields) level, not at the sample levels.
> 
> From what Eduard and you describe, the code you show is not the correct
> permutation. But I may have misunderstood your intention.
> 
> Also, be careful with permuted.index2 - there are reasons why it hasn't
> been integrated (design goals changed and we felt it would work best in
> a separate package that others could draw upon without loading all of
> vegan) and the code has festered a bit and may contain bugs - buyer
> beware!
> 
> G
> 
>> library(vegan)
>>
>> ### species matrix with 5 sp.
>> ### one env.variable
>> ### a factor denoting blocks of repeated measurments
>>
>> sp<-matrix(runif(24*3*5,0,100),24*3,5)
>> env<-rnorm(24*3,10,2)
>> rep.mes<-gl(24,3)
>>
>> ### NMDS:
>> sol<-metaMDS(sp,trymax=5)
>>
>> fit<-envfit(sol~env)
>> plot(sol)
>> plot(fit)
>>
>> ### testing code for appropiate randomization,
>> ### permuting blocks of 3 as a whole:
>> permuted.index2(nrow(sp),permControl(strata = rep.mes,permute.strata=T))

correctly, this should say:
### testing code for appropiate randomization,
### permuting within sites:
permuted.index2(nrow(sp),permControl(strata = rep.mes))

>> B=4999
>>
>> ### setting up frame for population of r2 values:
>> pop<-rep(NA,B+1)
>> pop[1]<-fit$vectors$r
>>

and:
>> ### loop:
>> for(i in 2:(B+1)){
>> fit.rand<-envfit(sol~env[permuted.index2(nrow(sp),
>>                           permControl(strata = rep.mes))])
>>            pop[i]<-fit.rand$vectors$r
>> }
>>
>> ### p-value:
 >> print(pval<-sum(pop>pop[1])/B+1)

here a bracket was missing:
print(pval<-sum(pop>pop[1])/(B+1))

>>
>> ### compare to anti-conservative p-value from envfit(),
>> ### not restricting permutations:
>>
>> envfit(sol~env,perm=B)
>>
>>
>> Zitat von Eduard Szöcs <szoe8822 at uni-landau.de>:
>>
>>> Thanks, that helped.
>>>
>>> permuted.index2() generates these types of permutations. But  
>>> envfit() does not use this yet.
>>> What if I modify vectorfit() (used by envfit() ) in such a way that  
>>> it uses permuted.index2() instead of permuted.index()?
>>>
>>>
>>> Eduard Szöcs
>>>
>>>
>>>
>>>
>>>
>>> Am 08.11.2010 22:01, schrieb Gavin Simpson:
>>>> On Mon, 2010-11-08 at 15:39 +0100, Eduard Szöcs wrote:
>>>>> Hi listers,
>>>>>
>>>>> I have species and environmental data for 24 sites that were sampled
>>>>> thrice. If I want to analyze the data with NMDS I could run metaMDS on
>>>>> the whole dataset (24 sites x 3 times = 72) and then fit environmental
>>>>> data, but this would be some kind of pseudoreplication given that the
>>>>> samplings are not independent and the gradients may be overestimated,
>>>>> wouldn`t it?
>>>>>
>>>>> For environmental data a factor could be included for the sampling
>>>>> dates - but this would not be possible for species data.
>>>>>
>>>>> Is there an elegant way either to aggregate data before ordination or
>>>>> to conduct sth. like a repeated measures NMDS?
>>>>>
>>>>> Thank you in advance,
>>>>> Eduard Szöcs
>>>> Depends on how you want to fit the env data - the pseudo-replication
>>>> isn't relevant o the nMDS. If you are doing it via function `envfit()`,
>>>> then look at argument `'strata'` which should, in your case, be set to a
>>>> factor with 24 levels. This won't be perfect because your data are a
>>>> timeseries and, strictly, one should permute them whilst maintaining
>>>> their ordering in time, but as yet we don't have these types of
>>>> permutations hooked into vegan.
>>>>
>>>> If you are doing the fitting some other way you'll need to include
>>>> "site" as a fixed effect factor to account for the within site
>>>> correlation.
>>>>
>>>> You don't need to worry about the species data and accounting for
>>>> sampling interval. You aren't testing the nMDS "axes" or anything like
>>>> that, and all the species info has been reduced to dissimilarities and
>>>> thence to a set of nMDS coordinates. You need to account for the pseudo
>>>> rep at the environmental modelling level, not the species level.
>>>>
>>>> HTH
>>>>
>>>> G
>>>>
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