[R-meta] meta-analysis with 2 within-subject variables

[zeffiro neurometrika.org]

Hi Wolfgang,

Thanks for looking at the problem. I expected that much of the answer lay in proper combination of the effects in escalc.

For the relatively simple example we want to explore, the behavioral measures are the same across the studies, are continuous, and all on the same scale - measureed using self-report scales of depression.

It is a cross-over design comparing treatment(N2O) to placebo, so each subject is measured 4 times over a course of 8-12 weeks -  pre/post treatment and in N2O/placebo conditions. We are interested in exploring the consistency of the treatment vs placebo effect across studies, properly accounting for the expected within-subject correlations.

Here is the data layout:
Author
Year
n.N2O
mean.pre.N2O
sd.pre.N2O
mean.post.N2O
sd.post.N2O
n.PLACEBO
mean.pre.PLACEBO
sd.pre.PLACEBO
mean.post.PLACEBO
sd.post.PLACEBO
Study
xxxx
20xx
14
19.1
4.25
12.1
7.28
15
17.1
8.87
11.7
5.89
1
...

So, to rephrase the question:

  *
How can escalc be used in this context to estimate the effect sizes, sampling variances and covariances for rma.mv()?
  *
What would the subsequent call to rma.mv() look like?

Regards,
Tom

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Today's Topics:

   1. Re: meta-analysis with 2 within-subject variables
      (Viechtbauer, Wolfgang (NP))

----------------------------------------------------------------------

Message: 1
Date: Fri, 6 Dec 2024 09:13:09 +0000
From: "Viechtbauer, Wolfgang (NP)"
        <wolfgang.viechtbauer using maastrichtuniversity.nl>
To: R Special Interest Group for Meta-Analysis
        <r-sig-meta-analysis using r-project.org>
Cc: zeffiro neurometrika.org <zeffiro using neurometrika.org>
Subject: Re: [R-meta] meta-analysis with 2 within-subject variables
Message-ID:
        <AS8PR08MB91934102416E6C639ADBAAC18B312 using AS8PR08MB9193.eurprd08.prod.outlook.com>

Content-Type: text/plain; charset="us-ascii"

Dear Tom,

I don't have any worked examples for this. However, before rma.mv(), the first step is the calculation of the effect sizes, their sampling variances, and covariances if there are multiple effect sizes for a given group. I assume you want to compute the pre-post change for each condition, so that would be two effects for a group. Is the response variable dichotomous or continuous? And if it is continuous, is the scale the same across studies (so one can stick to mean differences) or does it differ across studies (so one has to consider effect size measures that are comparable across different scales)?

Best,
Wolfgang

> -----Original Message-----
> From: R-sig-meta-analysis <r-sig-meta-analysis-bounces using r-project.org> On Behalf
> Of zeffiro neurometrika.org via R-sig-meta-analysis
> Sent: Tuesday, December 3, 2024 17:27
> To: r-sig-meta-analysis using r-project.org
> Cc: zeffiro neurometrika.org <zeffiro using neurometrika.org>
> Subject: [R-meta] meta-analysis with 2 within-subject variables
>
>  I have a question about how to set up the metafor code to perform a meta-
> analysis using an experimental design that is fairly common in cross-over
> treatment studies.
>
>  We have continuous outcome measures (mean and sd) from studies in which each
> participant was measured 4 times: 1) in both drug and placebo conditions and 2)
> both before and after exposure - in a cross-over design. So,
> each study is a 2x2 factorial design with 2 repeated measures.
>
> Although it looks to me as if rma.mv is the appropriate program for this
> analysis, I am having difficulty determining the syntax showing how to set
> things up to properly handle the within subject correlation and was hoping that
> someone could point me to a worked example to use as a guide. I have not found
> anything addressing meta-analysis modeling of multiple repeated measures in a
> single group.
>
> We are starting out with only 5 studies in the initial meta-analysis.
>
> Thanks in advance for any guidance you can provide.
>
> Regards,
> Tom




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