Hi Wojciech,
I just read (http://www.utsc.utoronto.ca/~04grycwo/overview.pdf) and
began thinking on your ideas.
Basically you are right, we need both methods: for advanced users and
for beginners. That's my point, too.
Regarding your concerns with importing the R-output back into Calc, I do
admit that there are some problems and issues to discuss. I will try to
think of the best solution.
Until then, I can give you some useful tips:
1. lets say we perform some calculations in R and store the output in a
new variable, e.g.
x <- fisher.test(matrix(c(40,60,30,70),2))
then we can get the output by typing at the prompt:> x
OR
we can get the length of the return object:
:> length(x)
<output> 7
and get every element individually from this output: (iterate
through x[[1]] -> x[[7]] )
:> x[[1]]
<output>> [1] 0.1819324 (this is the p-value)
2. I imagine statistical functions as belonging to 2 large groups (this
is NOT necessarily accurate BUT useful here):
a.) those that report a p-value as the main result
- this is usually the first value (aka x[[1]])
b.) those that perform more complex actions, like a multivariate
model, or a resampling, or graphic
These latter functions will be more difficult to deal with. But lets
stick now to the first group.
Hope this is helpful. I will try to work up a solution for the rest.
Sincerely,
Leonard
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