R help - Jun 2007 - anova on data means

I am transitioning from SAS to R and am struggling with a relatively simple
analysis.  Have tried Venables and Ripley and other guides but can't find a
solution.

I have an experiment with 12 tanks.  Each tank holds 10 fish.  The 12 tanks
have randomly assigned one of 4 food treatments - S(tarve), L(ow), M(edium)
and H(igh).  There are 3 reps of each treatment.  I collect data on size of
each fish at the end of the experiment.  So my data looks like

Tank  Trt   Fish   Size
1      S     1      3.4
1      S     2      3.6
....
1      S    10      3.5
2      L     1      3.4
....
12    M     10      2.1

To do the correct test of hypothesis using anova, I need to calculate the
tank means and use those in the anova.  I have tried using tapply() and by()
functions, but when I do so I "loose" the treatment level because it
is
categorical.  I have used 
Meandat<tapply(Size,list(Tank, Trt), mean)

But that doesn't give me a dataframe that I can then use to do the actual
aov analysis.  So what is the most efficient way to accomplish the analysis

Thanks

Tom Miller

Em Quinta 21 Junho 2007 16:56, Thomas Miller escreveu:
> I am transitioning from SAS to R and am struggling with a relatively simple
> analysis.  Have tried Venables and Ripley and other guides but can't
find a
> solution.
>
> I have an experiment with 12 tanks.  Each tank holds 10 fish.  The 12 tanks
> have randomly assigned one of 4 food treatments - S(tarve), L(ow), M(edium)
> and H(igh).  There are 3 reps of each treatment.  I collect data on size of
> each fish at the end of the experiment.  So my data looks like
>
> Tank  Trt   Fish   Size
> 1      S     1      3.4
> 1      S     2      3.6
> ....
> 1      S    10      3.5
> 2      L     1      3.4
> ....
> 12    M     10      2.1
>
> To do the correct test of hypothesis using anova, I need to calculate the
> tank means and use those in the anova.  I have tried using tapply() and
> by() functions, but when I do so I "loose" the treatment level
because it
> is categorical.  I have used
> Meandat<tapply(Size,list(Tank, Trt), mean)
>
> But that doesn't give me a dataframe that I can then use to do the
actual
> aov analysis.  So what is the most efficient way to accomplish the analysis
>
> Thanks
>
> Tom Miller
Tom,

try the aggregate funtion. Somethink like this

meandat <- aggregate(Size,list(Tank,Trt),mean)

Inte
Ronaldo
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