[R] Tukey HSD following lme

[Mark Difford]

Hi Christina,

>> How can this happen? How can the p-values from the Tukey become 
>> significant when the lme-model wasn't?

The link below, with an explanation by Prof. Fox is relevant to your
question:

http://www.nabble.com/Strange-results-with-anova.glm()-td13471998.html#a13475563

Another way to see the error of your ways is to fit your model using the
default treatment contrasts and then do a Dunnett post hoc using glht:

##
summary(glht(hc, linfct=mcp(CO2="Dunnett")))

Regards, Mark.


C.Schaedel wrote:
> 
> Hi everyone
> 
> I'm using Tukey HSD as post-hoc test following a lme analysis. I'm 
> measuring hemicelluloses in different species treated with three 
> different CO2 concentrations (l=low, m=medium, h=high). The whole 
> experiment is a split-plot design and the Tukey-function from the 
> package multcomp is suitable for lme-analysis with random factors.
> 
> The analysis works fine but I get a non significant lme-result and if I 
> do a Tukey afterwards (I know that one usually does a Tukey following a 
> significant anova-result) I get highly significant p-values for two 
> multiple comparisons.
> 
> How can this happen? How can the p-values from the Tukey become 
> significant when the lme-model wasn't?
> 
> 
> the data are: d
> 
>   Species  Block  CO2   hemicell
>   Ps         a     l    9.027363
>   Ps         b     l    9.647537
>   Ps         a     m   10.051916
>   Ps         b     m   10.112294
>   Ps         a     h   10.342162
>   Ps         b     h   10.303091
> 
> 
> my lme model: 
> anova(hc<-lme(asin(sqrt(0.01*hemicell))~CO2,random=~1|Block/CO2,data=d))
> 
>              numDF denDF   F-value p-value
> (Intercept)     1     2 30403.248  <.0001
> CO2             2     2     8.051  0.1105
> 
> 
> Tukey with the lme-object:
> 
> summary(glht(hc, linfct=mcp(CO2="Tukey")))
> 
> yielding:
> 
> Linear Hypotheses:
>             Estimate Std. Error z value p value
> m - l == 0 0.012616   0.004317   2.922 0.00963 **
> h - l == 0 0.016590   0.004317   3.843 < 0.001 ***
> h - m == 0 0.003973   0.004317   0.920 0.62738
> ---
> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> (Adjusted p values reported -- single-step method)
> 
> 
> Thank you very much for your help
> 
> Christina
> 
> 
> 
> -- 
> Christina Schädel
> Institute of Botany
> University of Basel
> Schönbeinstrasse 6
> CH-4056 Basel
> ph. +41 61 267 35 06
> fax +41 61 267 29 80
> E-Mail C.Schaedel at unibas.ch
> 
> ______________________________________________
> R-help at r-project.org mailing list
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
> 
> 

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