[R] ANOVA in Randomized-complete blocks design

[Simon Blomberg]

 You have mis-transcribed the data:

Series    Genotype    Weight
1            pb                0.986
3            bb                0.829

anova(aov(weight ~ series + genotype, data=dat))

gives the correct results when compared to S&R.

Cheers,

Simon.

January Weiner wrote:
> Dear all,
>
> I am trying to repeat an example from Sokal and Rohlfs "Biometry" --
> Box 11.4, example of a randomized-complete-blocks experiment.
>
> The data is fairly simple:
>
> series genotype weight
> 1     pp       0.958
> 1     pb       0.985
> 1     bb       0.925
> 2     pp       0.971
> 2     pb       1.051
> 2     bb       0.952
> 3     pp       0.927
> 3     pb       0.891
> 3     bb       0.892
> 4     pp       0.971
> 4     pb       1.010
> 4     bb       0.955
>
> The model used for ANOVA in the book is
>
> Y_{ij} = \mu + \alpha_i + B_i + [(\alpha B)_{ij}] + \epsilon_{ij}
>
> (I am not quite confident how to represent this model in R, see below)
>
> The ANOVA table from S&R looks like this:
>
> MSB    series         3   0.021  0.007  10.23 **
> MSA    genotypes  2   0.010  0.005   6.97 *
> MSE    error           6   0.004  0.001
>
> In R, I am using the following model (is this correct?)
>
> aov.ob = aov( genotype ~ genotype + series )
>
> However, my results are
>
>             Df    Sum Sq   Mean Sq F value  Pr(>F)
> series       3 0.0135867 0.0045289  6.6360 0.02469 *
> genotype     2 0.0056732 0.0028366  4.1563 0.07367 .
> Residuals    6 0.0040948 0.0006825
>
> What am I doing wrong?
>
> Regards,
> January
>
> --
>
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>
>   


-- 
Simon Blomberg, B.Sc.(Hons.), Ph.D, M.App.Stat. 
Centre for Resource and Environmental Studies
The Australian National University              
Canberra ACT 0200                               
Australia                                       
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The combination of some data and an aching desire for 
an answer does not ensure that a reasonable answer 
can be extracted from a given body of data.
- John Tukey.