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.viechtbauer@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-bounces@r-project.org [mailto:r-help-bounces@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.sylvestre@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.



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