[R-sig-eco] R-sig-ecology Digest, Vol 39, Issue 16

Kay Cecil Cichini Kay.Cichini at uibk.ac.at
Mon Jun 27 12:36:07 CEST 2011


hi,

sorry - i'm afraid this was only due to a trivial syntax error:  
"...,dist = "euclidean",..." should say "...,method = "euclidean",..."  
with the wrong argument adonis defaults to "bray" - and with  
bray-curtis dissim. the difference between 1 and 2 is really not the  
same as the one between 2 and 3 or 4 and 5, isn't it?

so the message to you, regarding your suspicious p-values, might be to  
check for the dissimilarity-index you use, what its characteristics  
are and if it's appropriate for the questions you ask..

yours,
kay

following up my example:

# distance matrix with bray-curtis dissimilarity:
# dissimilarities *are the same*

dm <- as.matrix(vegdist(spdf, method = "bray"))

# assign names
dimnames(dm) <- list(paste(treat, imp), paste(treat, imp))

# see average off-diagonal dissimilarities (within treatments, between  
impact levels)
mean(dm[11:20,1:10])
mean(dm[31:40,21:30])
mean(dm[51:60,41:50])

# distance matrix with euclidean dissimilarity:
dm <- as.matrix(vegdist(spdf, method = "euclidean"))

# assign names
dimnames(dm) <- list(paste(treat, imp), paste(treat, imp))

# see average off-diagonal dissimilarities (within treatments, between  
impact levels)
# dissimilarities *are not the same*
mean(dm[11:20,1:10])
mean(dm[31:40,21:30])
mean(dm[51:60,41:50])




Zitat von Kari Lintulaakso <kari.lintulaakso at gmail.com>:

> Hi Kay,
>
> I also get significant values (both from adonis and anova) when
> running your code. I'm currently running my own adonis analysis which
> most have significant results (this has been worrying me for some
> time).
> I do recall some R discussion about general R setting/value which
> might set all the values analysed to be logarithmic. If there is this
> kind of setting, does anyone know what it is and how to set it off?
> I'm using Revolution R Enterprise 4.3.0 (14.4.2011) Academic version,
> R version 2.12.2 (2011-02-25)
> -Kari
>
> My results:
> for (i in 1:4) {print(summary(aov(spdf[, i] ~ treat * imp)))}
>             Df  Sum Sq Mean Sq   F value Pr(>F)
> treat        2 166.017  83.008 1316.5029 <2e-16 ***
> imp          1  15.978  15.978  253.4022 <2e-16 ***
> treat:imp    2   0.021   0.011    0.1666  0.847
> Residuals   54   3.405   0.063
> ---
> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
>             Df  Sum Sq Mean Sq   F value Pr(>F)
> treat        2 155.836  77.918 1323.0303 <2e-16 ***
> imp          1  13.185  13.185  223.8864 <2e-16 ***
> treat:imp    2   0.237   0.119    2.0159 0.1431
> Residuals   54   3.180   0.059
> ---
> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
>             Df  Sum Sq Mean Sq   F value  Pr(>F)
> treat        2 158.672  79.336 1091.8367 < 2e-16 ***
> imp          1  16.069  16.069  221.1473 < 2e-16 ***
> treat:imp    2   0.363   0.182    2.4987 0.09165 .
> Residuals   54   3.924   0.073
> ---
> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
>             Df  Sum Sq Mean Sq F value Pr(>F)
> treat        2 159.194  79.597 943.528 <2e-16 ***
> imp          1  14.289  14.289 169.383 <2e-16 ***
> treat:imp    2   0.093   0.047   0.554 0.5779
> Residuals   54   4.555   0.084
> ---
> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
>>
>> RevoMods:::revoFix(x)adonis(spdf ~ treat * imp, dist = "euclidean")
>
> Call:
> adonis(formula = spdf ~ treat * imp, dist = "euclidean")
>
>           Df SumsOfSqs MeanSqs F.Model      R2 Pr(>F)
> treat      2    3.4133 1.70666  640.19 0.80850  0.001 ***
> imp        1    0.3150 0.31504  118.18 0.07462  0.001 ***
> treat:imp  2    0.3495 0.17473   65.54 0.08278  0.001 ***
> Residuals 54    0.1440 0.00267         0.03410
> Total     59    4.2218                 1.00000
>
>
> On Sun, Jun 26, 2011 at 8:00 PM,   
> <r-sig-ecology-request at r-project.org> wrote:
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>>   1. Re: adonis question (Kay Cecil Cichini)
>>
>>
>> ----------------------------------------------------------------------
>>
>> Message: 1
>> Date: Sat, 25 Jun 2011 12:20:44 +0200
>> From: Kay Cecil Cichini <Kay.Cichini at uibk.ac.at>
>> To: Etienne Laliberte <etiennelaliberte at gmail.com>
>> Cc: r-sig-ecology at r-project.org
>> Subject: Re: [R-sig-eco] adonis question
>> Message-ID: <20110625122044.68992dwaacyxu6ps at web-mail.uibk.ac.at>
>> Content-Type: text/plain; charset=ISO-8859-1; DelSp="Yes";
>>        format="flowed"
>>
>> hello etienne,
>>
>> i tried many times and it's alway significant.
>>
>> i also added:
>>
>> par(mfrow = c(2, 2))
>> for (i in 1:4) {print(interaction.plot(treat, imp, spdf[, i]))}
>>
>> ...that did not show an interaction for any set of random numbers i tried.
>>
>> yours,
>> kay
>>
>> Zitat von Etienne Laliberte <etiennelaliberte at gmail.com>:
>>
>>> Dear Kay,
>>>
>>> I ran your code and found no significant interactions. You just got
>>> "unlucky" with rnorm(), as can happen. Try it again.
>>>
>>> Cheers,
>>>
>>> Etienne
>>>
>>> -----Original Message-----
>>> From: r-sig-ecology-bounces at r-project.org
>>> [mailto:r-sig-ecology-bounces at r-project.org] On Behalf Of Kay Cecil Cichini
>>> Sent: Friday, 24 June 2011 9:31 PM
>>> To: r-sig-ecology
>>> Subject: [R-sig-eco] adonis question
>>>
>>> hi all,
>>>
>>> i played around with adonis and came across a result that i can't
>>> explain - more precisely i get a sign interaction-effect where i
>>> suppose there should be none:
>>>
>>> library(vegan)
>>>
>>> # species matrix/df
>>> spdf <- matrix(NA, 60, 4, dimnames = list(1:60, c("sp1", "sp2", "sp3",
>>> "sp4")))
>>> spdf <- as.data.frame(spdf)
>>>
>>> # 1st factor = treatment:
>>> treat <- gl(3, 20, labels = paste(1:3, "t", sep=""))
>>>
>>> # 2nd factor = impact:
>>> imp <- rep(gl(2, 10, labels = c("yes", "no")), 3)
>>>
>>> # simulating effect -
>>> # simulation will add similar effect
>>> # across level combinations, no interactions:
>>> eff <- sort(rep(1:6, 10))
>>>
>>> # add random noise:
>>> spdf$sp1 = eff + rnorm(60, 0, 0.25)
>>> spdf$sp2 = eff + rnorm(60, 0, 0.25)
>>> spdf$sp3 = eff + rnorm(60, 0, 0.25)
>>> spdf$sp4 = eff + rnorm(60, 0, 0.25)
>>>
>>> # difference imp:yes vs imp:no is the same across all levels of treatment
>>> aggregate(sp1 ~ imp * treat, data = spdf, FUN = mean)
>>>
>>> # univariate ANOVAs with no interactions, as expected:
>>> for (i in 1:4) {print(summary(aov(spdf[, i] ~ treat * imp)))}
>>>
>>> # PERMANOVA - strangly gives sign. interaction (??)
>>> adonis(spdf ~ treat * imp, dist = "euclidean")
>>>
>>> thanks in advance,
>>> kay
>>>
>>> _______________________________________________
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>>> R-sig-ecology at r-project.org
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>>
>>
>>
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>> End of R-sig-ecology Digest, Vol 39, Issue 16
>> *********************************************
>>
>
>
>
> --
> Kari Lintulaakso, M.Sc.(Biosciences)
>
> Doctoral student
> Paleontology and Paleoecology
> Department of Geosciences and Geography
> University of Helsinki
>
> * Mobile: +358 50 40 33391
> * Office:  +358 9 191 50842
> * Email: kari.lintulaakso at helsinki.fi
> * Post: Department of Geology, Gustaf Hällströmin katu 2a (P.O Box
> 64), 00014 University of Helsinki
> * Web page: http://blogs.helsinki.fi/lintulaa/
>
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