Hi, I am dealing with the following problem. There are two biochemical assays, say A and B, available for analyzing blood samples. Half the samples have been analyzed with A. Now, for some insurmountable logistic reasons, we have to use B to analyze the remaining samples. However, we can do a comparative study on a small number of samples where we can obtain concentrations using both A and B. This gives us the data of the form (x, y), where x are values from A and y from B. Now, my question: Can we simply use the regression equation from regressing y on x, to convert all the x values for which only method A was used? Or do we need to obtain the functional (or structural) relationship between X and Y (the true values without measurement error) and use that to do this conversion. It seems to me that since we can only observe error-prone x, and we should be predicting the expected value of error-prone y (i.e E[y | x]). Therefore, we can simply use the ordinary regression equation. However, I have seen papers using the Deming's orthogonal regression or something equivalent in the clinical chemistry literature to address this problem. Deming's method would make sense if I am interested in obtaining the functional relationship between X and Y (the true values of two assays), but I don't see why I should care about that. Am I right? I would appreciate any clarifying thoughts on this. I apologize for posting this methodological, non-R question. Thank you, Ravi. ---------------------------------------------------------------------------- -------
Ravi Varadhan, Ph.D. Assistant Professor, The Center on Aging and Health Division of Geriatric Medicine and Gerontology Johns Hopkins University Ph: (410) 502-2619 Fax: (410) 614-9625 Email: [EMAIL PROTECTED] Webpage: http://www.jhsph.edu/agingandhealth/People/Faculty/Varadhan.html ---------------------------------------------------------------------------- -------- [[alternative HTML version deleted]] ______________________________________________ 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.
