For some reason I was under the false impression that these packages were made for meta-analyses of RCT-like studies in which two groups are compared. I am glad to see that I was wrong and that I can use one of these packages.
All studies reported using the same units for the exposure so the OR are comparable. Thanks for your responses, MP Le , "Viechtbauer Wolfgang (STAT)" <wolfgang.viechtba...@maastrichtuniversity.nl> a écrit : > I do not see any major difficulties with this case either. Suppose you > have OR = 1.5 (with 95% CI: 1.19 to 1.90) indicating that the odds of a > particular outcome (eg, disease) is 1.5 times greater when the > (continuous) exposure variable increases by one unit. Then you can > back-calculate the SE of log(OR) = .41 with > sei = (ln(ci.ub) - ln(ci.lb)) / (2*1.96), > which in this case is approximately 0.12. The sampling variance of > log(OR) is then vi = sei^2. > Now you have everything for the meta-analysis, using any of the packages > mentioned. > What Thomas already mentioned is that the 'one unit increase' must mean > the same thing in each study. Therefore, if the exposure variable is > measured in months in one study and in years in another study, then the > odds ratios are obviously not directly comparable. If the units are just > multiples of each other, then you can easily calculate what the OR would > be when putting the exposure variable on the same scale. For example, an > OR of 1.5 for a one month increase in exposure is the same as an OR of > 1.5^12 = 129.75 for a one year increase in exposure. > Best, > Wolfgang > -- > Wolfgang Viechtbauer, Ph.D., Statistician > Department of Psychiatry and Psychology > School for Mental Health and Neuroscience > Faculty of Health, Medicine, and Life Sciences > Maastricht University, PO Box 616 (VIJV1) > 6200 MD Maastricht, The Netherlands > +31 (43) 388-4170 | http://www.wvbauer.com > > -----Original Message----- > > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] > > On Behalf Of Thomas Lumley > > Sent: Wednesday, April 04, 2012 23:42 > > To: Marie-Pierre Sylvestre > > Cc: r-help@r-project.org > > Subject: Re: [R] meta-analysis, outcome = OR associated with a > continuous > > independent variable > > > > On Thu, Apr 5, 2012 at 8:24 AM, Marie-Pierre Sylvestre > > mp.sylves...@gmail.com> wrote: > > > Hello everyone, > > > I want to do a meta-analysis of case-control studies on which an OR > > > was computed based on a continuous exposure. I have found several > > > several packages (metafor, rmeta, meta) but unless I misunderstood > > > their main functions, it seems to me that they focus on two-group > > > comparisons (binary independent variable), and do not have the option > > > of using a continuous independent variable. > > > > > > There's no problem in using continuous exposures in meta.summaries() in > > the rmeta package. For each study, compute your log odds ratio and its > > standard error, and feed them in. > > > > You just need to make sure that the odds ratio is in the same units in > > each study, of course. > > > > -thomas > > > > -- > > Thomas Lumley > > Professor of Biostatistics > > University of Auckland > > > > ______________________________________________ > > 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. [[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.
