[R-sig-eco] interpreting adonis results

[yy.loh at york.ac.uk]

Thanks all for your help on adonis！！！^_^
Thanks Kay too...;-)


So,I have moved on and currently working on betadisper and faced some 
problems.

1.In vegatutor.pdf, betadisper (pg 33), "The function can only use one 
factor as an independent variable, and it does not know the formula 
interface,..."
 
mod <- with(dune.env, betadisper(betad, Management))

Let's say I need to investigate the interaction of factors: Management and 
USE. My question is: Can i create a new factor from the interaction of 
factor Management and USE then use it in betadisper()? E.g.

groupA<-interaction(dune.env$Management,dune.env$Use)
mod <- with(dune.env, betadisper(betad, groupA))
mod

Error in optim(apply(X, 2, median, na.rm = TRUE), fn = medfun, gr = 
dmedfun, :
  non-finite value supplied by optim

For the dune dataset, the above error occured. But for my data, the 
interaction works. I wonder if i continue to use the new factor generated 
from the factor-interaction for the betadisper, will it affects the 
results? If this is wrong, what would be the recommended function to use?

Sincerely Yours,
J

On Nov 17 2011, Kay Cecil Cichini wrote:

>..to be save I would consider to exclude an effect due to different  
>multivariate spread. See chapter 5.2, Homogeneity of groups and beta  
>diversity, in the vegan tutorial at  
>http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf.
>
>best,
>kay
>
>
>Zitat von Gavin Simpson <gavin.simpson at ucl.ac.uk>:
>
>> On Wed, 2011-11-16 at 03:43 +0100, Gian Maria Niccolò Benucci wrote:
>>> Hi all,
>>>
>>> I had 84 samples collected in 7 different sites. In each sample were 
>>> individuated the different fungal species and recorded. I would test if 
>>> exist a real difference between the sites and if exist a sort of site 
>>> effect that structure the fungal communities... Then, I did adonis test
>>>
>>> > adonis(community.sq ~ location, data=env.table, permutations=999)
>>>
>>> Call: adonis(formula = community.sq ~ location, data = env.table, 
>>> permutations = 999)
>>>
>>>           Df SumsOfSqs MeanSqs F.Model      R2 Pr(>F)
>>> location   6    12.593 2.09886  6.8867 0.34922  0.001 ***
>>> Residuals 77    23.467 0.30477         0.65078
>>> Total     83    36.060                 1.00000
>>> ---
>>> Signif. codes:  0 *** 0.001 ** 0.01 * 0.05 . 0.1   1
>>>
>>>
>>>
>>> The significance is R2=0.349 at P=0.001 Can I assure that exist a 
>>> strong site effect in structuring the communities in each site?
>>
>> Depends. The test is one of no effect of `location`. You have found
>> evidence against this hypothesis and thus could reject this hypothesis,
>> instead accepting the alternative hypothesis that there is an effect of
>> `location`. As to the strength of this effect? ~35% of the sums of
>> squares can be explained by `location`. Substantially more of the
>> variance remains unexplained. As I know nothing about your subject area,
>> I am unable to comment further on the strength of the relationship.
>>
>> Seeing as many ecologists whose work I read would say an effect is
>> significant if the p-value was >= 0.05. Not that I subscribe to this way
>> or working, but by that criterion, you have identified a significant
>> `location` effect.
>>
>> HTH
>>
>> G
>>
>>>
>>> Thanks for helping,
>>>
>>> G.
>>>
>>> 	[[alternative HTML version deleted]]
>>>
>>> _______________________________________________
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>>
>> --
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>>  Dr. Gavin Simpson             [t] +44 (0)20 7679 0522
>>  ECRC, UCL Geography,          [f] +44 (0)20 7679 0565
>>  Pearson Building,             [e] gavin.simpsonATNOSPAMucl.ac.uk
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-- 
Loh Yen Yee
Department of Biology (Area 18)
University of York
York, UK YO10 5DD