[R] Comparing samples with widely different uncertainties

[Sandy Small]

Hi
This is probably more of a statistics question than a specific R
question, although I will be using R and need to know how to solve the
problem in R.

I have several sets of data (ejection fraction measurements) taken in
various ways from the same set of (~400) patients (so it is paired data).
For each individual measurement I can make an estimate of the percentage
uncertainty in the measurement.
Generally the measurements in data set A are higher but they have a
large uncertainty (~20%) while the measurements in data set Bare lower
but have a small uncertainty (~4%).
I believe, from the physiology, that the true value is likely to be
nearer the value of A than of B.
I need to show that, despite the uncertainties in the measurements
(which are not themselves normally distributed), there is (or is not) a
difference between the two groups, (a straight Wilcoxon signed ranks
test shows a difference but it cannot include that uncertainty data).

Can anybody suggest what I should be looking at? Is there a language
here that I don't know? How do I do it in R?
Many thanks for your help
Sandy

--

Sandy Small
Clinical Physicist
NHS Greater Glasgow and Clyde
and
NHS Forth Valley

Phone: 01412114592
E-mail: Sandy.Small at NHS.net


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