# [R] anova

Lynn Govaert lynn.govaert at gmail.com
Thu Aug 21 12:13:13 CEST 2014

```I pressed enter to soon.

Again

Hi all,

I have troubles with doing an anova. So I have the following variables: a
variable group with two levels, a continuous variable trait and within each
group we have 12 organisms (clone) and for each clone we have 5 replicates.
So we want to see if for the variable trait the two groups differ,
including the information for the clones.

So the dataset looks like:

trait          group            clone
...              1                   a1
...              1                   a2
...
...              1                   a12
...              1                    a1
...
...               2                    b1
...               2                    b2

etc

trait are just some numbers.
So clone is nested in group.

Then I don't understand how to make the anova,
I was thinking we want to see if there is an effect of group

So we built the model aov(trait ~group)
but because we also want to include the effect of clone which is a random
effect we do

aov(trait ~ group + Error(clone))
but because Clone is nested in group
we do
aov(trait ~ group + Error(group/clone))

but if I do this I get the following output

Error: PopulationTNFMF
Df  Sum Sq Mean Sq
PopulationTNFMF  1 0.00917 0.00917

Error: PopulationTNFMF:CloneTNFMF
Df    Sum Sq   Mean Sq F value Pr(>F)
Residuals  1 0.0001849 0.0001849

Error: Within
Df  Sum Sq   Mean Sq F value Pr(>F)
Residuals 117 0.02107 0.0001801

and I don't get any p-values, so I guess I'm doing something wrong.
Can someone help?

Thank you in advance
Lynn

2014-08-21 12:08 GMT+02:00 Lynn Govaert <lynn.govaert at gmail.com>:

> Hi all,
>
> I have troubles with doing an anova. So I have the following variables: a
> variable group with two levels, a continuous variable trait and within each
> group we have 12 organisms (clone) and for each clone we have 5 replicates.
> So we want to see if for the variable trait the two groups differ,
> including the information for the clones.
>
> So the dataset looks like:
>
> trait          group
>

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