[R-sig-ME] GLM: Difference between treatment groups for each colony (Tukey posthoc test)

[paul debes]

Hi Sophie and List,

If you are interested in the treatment contrasts for each level of the  
Colony factor (with three levels), it may be better to view your  
experiment as a factorial and specify a simple linear model rather than  
the presently specified linear mixed model. A random Colony term with only  
three levels may also not provide the best estimate for the correlation of  
colony data between treatments (i.e., as intraclass correlation) that is  
taken into account when testing the general treatment term.

Would this work for you?:

fit_life = lm(last.scan ~ 1 + treatment*colony, data = data)

In case the treatment:colony term is significant you could conduct the  
additional pairwise tests of interest.

Best,
Paul



On Mon, 07 Dec 2015 13:02:36 +0200, Sophie Waegebaert  
<sophie.waegebaert at gmail.com> wrote:

> Hi,
>
> I'm still learning how to use R and I have some trouble making using  
> Tukey
> posthoc tests. I have a dataset with 3 colonies (A, B and C). Each colony
> is divided into 2 treatments: control and DWV. I want to run a GLM to  
> test
> wether there is a difference in life expectancy (last.scan) between the
> treatment groups for each of the colonies, but I do not know if I am  
> using
> the right strategy.
>
> I have taken 'treatment' as a fixed factor and 'colony' as a random  
> factor:
>
> fit_life = lmer(last.scan~treatment + (1|colony), data =
> data)Anova(fit_life, type = 3) # Type of treatment has a significant
> effect on on the life expectancy.
>     Response: last.scan
>           Chisq Df Pr(>Chisq)
>     (Intercept) 106.976  1  < 2.2e-16 ***
>     treatment    25.373  1  4.724e-07 ***
>
> And this is the code I use to do a Tukey posthoc test:
>
> mcp = glht(fit_life, linfct = mcp(treatment = "Tukey"))
> summary(mcp)# DWV treatment significantly changes life expectancy (z =
> -9.734, p = < 2e-16)
>
> Is it possible to find the difference for each colony?
>
> Thanks a lot for an explanation or hint!
>
> Cheers,
>
> Sophie
>
> 	[[alternative HTML version deleted]]
>
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-- 
Paul Debes
DFG Research Fellow
University of Turku
Department of Biology
Itäinen Pitkäkatu 4
20520 Turku
Finland