[R] How to store the results of multiple iterations of 'aov' in a data.frame?

[Michal Figurski]

A follow-up to "Need to calculate within- and between-run CV"

I have a dataset of 210 Samples, of which each was run several times in 
several consecutive days. A dataset for one sample is below:

qu.s <-
structure(list(Sample = c(44L, 44L, 44L, 44L, 44L, 44L, 44L,
44L, 44L, 44L), Run = c(1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L
), Rep = c(1, 2, 1, 2, 3, 4, 1, 2, 3, 4), value = c(120L, 107L,
117L, 124L, 118L, 127L, 110L, 113L, 109L, 113L)), .Names = c("Sample",
"Run", "Rep", "value"), row.names = c(1L, 2L, 3L, 4L,
5L, 6L, 7L, 8L, 9L, 10L), class = "data.frame")

and the code I used is below:

a=aov(value ~ Run, data=qu.s)						

I assume that 'Residual' is the variance between replicates in my data.
Since I have to run the above code 210 times, my question is: how to 
store the results of 'aov' in a separate data.frame?

For each iteration of 'aov' I need to store: the _sums of squares_ for 
Run and Residual, the _N_ of replicates and the _mean_. Later I want to 
use it to calculate the coefficients of variation (CV) for each sample.

I looked at the structure of aov object, but the sums of squares are not 
listed there, though 'summary(a)' prints them. Please help.

--
Michal Figurski


Michal Figurski wrote:
> Dear R-helpers,
> 
> I have a dataset named "qu", organized as follows:
> 
> Sample    Run    Replicate    Value
> 1    1    1        25
> 1    1    2        40
> 1    1    3        33
> 1    1    4        29
> 1    2    1        37
> 1    2    2        44
> 1    2    3        45
> 1    3    1        25
> 1    3    2        40
> 1    4    1        33
> 1    4    2        29
> 1    4    3        25
> 2 ...
> 
> Basically, a sample was run on an assay multiple times within a single 
> day. Each of these results is "Replicate". Then run was repeated several 
> times in consecutive days - variable "Run". There are 210 such samples.
> 
> I need to actually calculate the CV for each sample:
>  - within run (between replicates) - that's easy to do in Excel
>  - between run - that's the problem.
> 
> I was thinking of using either 'aov' or 'lme' to solve this. However, I 
> don't know how to interpret the output. For example, a summary output 
> from "aov(Value~Run+Replicate, subset(qu,Sample==79))' for one sample was:
> 
>             Df Sum Sq Mean Sq F value Pr(>F)
> Run          1  4.000   4.000  0.3214 0.6104
> Replicate    1 73.500  73.500  5.9062 0.0933 .
> Residuals    3 37.333  12.444
> ---
> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> 
> Do you guys think this is correct approach?
> How do I extract these numbers (sum of squares) to store in a separate 
> dataframe for further calculations?
> 
> And how should I interpret the "Residual" in this setting?
> 
> I will appreciate your comments.
>