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.
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