On Aug 25, 2010, at 8:57 AM, Sandy Small wrote: > 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
The first place that I would start is at Martin Bland's page pertaining to the design and analysis of measurement studies: http://www-users.york.ac.uk/~mb55/meas/meas.htm The papers he co-authored with Doug Altman are the "go to" resource for this domain. HTH, Marc Schwartz ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
