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From | guhjy@kmu.edu.tw |
To | statalist@hsphsun2.harvard.edu |
Subject | Re: st: Is it valid to use the individual ratios (i.e. Xi/Yi) in the dependent or independent part of a regression model? |
Date | Sun, 27 May 2012 17:07:52 +0800 |
Dear David: In a sample (not a survey sample) of about 500 hospital chronic kidney disease patients, I am using ACR as the: 1. Dependent variable: regress ACR age gender cholesterol (Is it better to regress urinary albumin on urinary creatinine, age, gender and cholesterol?) 2. Independent variable: regress cholesterol age gender ACR (Is it better to regress cholesterol on age, gender, urinary albumin and urinary creatinine?) "Patients with chronic kidney disease" is the population in the inferential statistics. The population ACR (but not the population totals of urinary albumin or urinary creatinine) are my concerns. Thank you. Jinn-Yuh 2012/5/27 David Hoaglin <dchoaglin@gmail.com>: > Dear Jinn-Yuh, > > In a notation that is customary in survey sampling, X/Y (perhaps more > commonly Y/X) is the ratio of two population totals. Please tell us > more about the population for which you would like to estimate the > ratio of the population total of urinary albumin to the population > total of urinary creatinine. > > If you are calculating ACR for individual patients, and that is the > variable that you are using in your regressions, how are the > population totals related to those regressions? The relevance of the > biases that you have mentioned to your analysis is not yet clear. It > would help if you described one of the multiple regression models that > you are using. > > David Hoaglin > > On Sat, May 26, 2012 at 9:02 PM, <guhjy@kmu.edu.tw> wrote: >> ACR (urinary albumin creatinine ratio, i.e. urinary albumin [Xi] >> divided by urinary creatinine [Yi]) is used to standardize for urinary >> concentration to ensure comparability of albuminuria among individual >> patients (http://en.wikipedia.org/wiki/Microalbuminuria). I am using >> ACR as the dependent or independent variable in multiple linear >> regressions. However, "ratio of means" and "mean of ratios (ACR >> [Xi/Yi] in this case)" are both biased estimates for the population >> ratio [X/Y] (Mean of ratios or ratio of means or both?: >> http://www.sciencedirect.com/science/article/pii/S0378375801001811). >> In view of these problems and the many pitfalls of ratios mentioned in >> many references, is it better to use X (or Y) to adjust for Y (or X) >> in regressions (despite its clinical usefulness in individual >> decisions)? >> >> Thank you. >> Jinn-Yuh > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/