[R-meta] Difference between subset (in a loop) and mods in metafor rma.mv

[Reza Norouzian]

Also, Brenden, if you want to replicate the results from when you subset
the data (i.e., not allowing the borrowing of info.) with a single model,
then you can do:

rma.mv(yi~Predictor+0, vi, random = list(~Predictor | Study, ~Predictor |
Article),
       struct = c("DIAG","DIAG"), data=dat)

which for your toy dataset, where predictor's categories have no
heterogeneity at the Article level, may be reduced to:

rma.mv(yi~Predictor+0, vi, random = ~Predictor | Study,
       struct = "DIAG", data=dat)

This topic has come up on the list a number of times, you may want to scan
through the listserv's archives for related examples (e.g.,
https://stat.ethz.ch/pipermail/r-sig-meta-analysis/2022-June/004074.html).

Reza


On Fri, Sep 29, 2023 at 11:25 AM Viechtbauer, Wolfgang (NP) via
R-sig-meta-analysis <r-sig-meta-analysis using r-project.org> wrote:

> Yes. For some relevant literature, see for example:
>
> Riley, R. D., Abrams, K. R., Lambert, P. C., Sutton, A. J., & Thompson, J.
> R. (2007). An evaluation of bivariate random-effects meta-analysis for the
> joint synthesis of two correlated outcomes. Statistics in Medicine, 26(1),
> 78-97. https://doi.org/10.1002/sim.2524
>
> Jackson, D., White, I. R., Price, M., Copas, J., & Riley, R. D. (2017).
> Borrowing of strength and study weights in multivariate and network
> meta-analysis. Statistical Methods in Medical Research, 26(6), 2853-2868.
> https://doi.org/10.1177/0962280215611702
>
> Copas, J. B., Jackson, D., White, I. R., & Riley, R. D. (2018). The role
> of secondary outcomes in multivariate meta-analysis. Journal of the Royal
> Statistical Society, Series C, 67(5), 1177-1205.
> https://doi.org/10.1111/rssc.12274
>
> Best,
> Wolfgang
>
> >-----Original Message-----
> >From: R-sig-meta-analysis [mailto:
> r-sig-meta-analysis-bounces using r-project.org] On
> >Behalf Of Brendan Pearl via R-sig-meta-analysis
> >Sent: Friday, 29 September, 2023 13:56
> >To: R Special Interest Group for Meta-Analysis
> >Cc: Brendan Pearl
> >Subject: Re: [R-meta] Difference between subset (in a loop) and mods in
> metafor
> >rma.mv
> >
> >Thankyou Wolfgang,
> >
> >Just for my understanding: "When using the full dataset and using
> 'Predictor' as
> >a moderator, then it is possible for information to be shared/borrowed
> from both
> >levels of the moderator within studies." - is this what occurs in a
> >multivariable/multivariate meta-analysis?
> >
> >Regards,
> >Brendan.
> >
> >------- Original Message -------
> >On Friday, September 29th, 2023 at 8:56 PM, Viechtbauer, Wolfgang (NP)
> ><wolfgang.viechtbauer using maastrichtuniversity.nl> wrote:
> >
> >> Dear Brendan,
> >>
> >> Both approaches fit multilevel models. The difference arises because of
> two
> >reasons:
> >>
> >> 1) When using the full dataset and using 'Predictor' as a moderator,
> then it is
> >possible for information to be shared/borrowed from both levels of the
> moderator
> >within studies.
> >>
> >> 2) When subsetting based on 'Predictor', you allow the variance
> components to
> >differ across the two levels of the moderator. This is essentially what is
> >discussed here:
> >>
> >>
> https://www.metafor-project.org/doku.php/tips:comp_two_independent_estimates
> >>
> >> but in the context of a simpler model.
> >>
> >> Best,
> >> Wolfgang
> >>
> >> > -----Original Message-----
> >> > From: R-sig-meta-analysis [mailto:
> r-sig-meta-analysis-bounces using r-project.org]
> >On
> >> > Behalf Of Brendan Pearl via R-sig-meta-analysis
> >> > Sent: Friday, 29 September, 2023 12:00
> >> > To: r-sig-meta-analysis using r-project.org
> >> > Cc: Brendan Pearl
> >> > Subject: [R-meta] Difference between subset (in a loop) and mods in
> metafor
> >> > rma.mv
> >> >
> >> > I am trying to understand the difference using the 'subset' and 'mods'
> >options in
> >> > rma.mv.
> >> >
> >> > I have run two analyses using rma.mv on the same dataset that has a
> three
> >level
> >> > structure (articles nested within larger studies) and get different
> results.
> >> >
> >> > In the first example I have given below, is looping over rma.mv and
> passing a
> >> > different predictor to the subset option a univariate meta-analysis?
> And in
> >the
> >> > second example, is passing the predictor to the mods option running a
> >> > multivariable meta-analysis?
> >> >
> >> > Study <- c("A","A","B","C","C","D","E","F","F","G")
> >> > Article <- c("1","2","3","4","5","6","7","8","9","10")
> >> > Predictor <- c("x","x","x","y","y","y","x","x","y","y")
> >> > yi <- c(-.2,-.3,-.8,.5,.6,.4,-.1,-.8,.3,.8)
> >> > vi <- c(.01,.01,.01,.01,.01,.01,.01,.01,.01,.01)
> >> >
> >> > dat <- data.frame(Study,Article,Predictor,yi,vi)
> >> >
> >> > #FIRST EXAMPLE#Subset analyses
> >> > # gives me
> >> >
> >> > #1 x OR = -0.49 [-0.84, -0.13]
> >> > #2 y OR = 0.51 [0.31, 0.72]
> >> >
> >> > df_subset <-
> data.frame(val=as.character(),subset_result=as.character())
> >> >
> >> > for (val in unique(dat$Predictor)){
> >> >
> >> > res_univariate <- rma.mv(yi=yi,
> >> > V=vi,
> >> > data=dat,
> >> > random = ~1 | Study/Article,
> >> > subset = Predictor == val,
> >> > method = "REML"
> >> > )
> >> >
> >> > result <- capture.output(cat(
> >> > "OR = ",
> >> > format(round(res_univariate$beta, 2),nsmall = 2),
> >> > " [",
> >> > format(round(res_univariate$ci.lb, 2),nsmall = 2),
> >> > ", ",
> >> > format(round(res_univariate$ci.ub, 2),nsmall = 2),
> >> > "]",
> >> > sep=""
> >> > )
> >> > )
> >> >
> >> > df_subset[nrow(df_subset) +1,] = c(
> >> > val,
> >> > result
> >> > )
> >> >
> >> > }
> >> >
> >> > #SECOND EXAMPLE
> >> > #Mod analysis
> >> > #gives me:
> >> >
> >> > # estimate ci.lb ci.ub
> >> >
> >> > #factor(Predictor)x -0.4825 -0.7246 -0.2404
> >> > #factor(Predictor)y 0.5807 0.3386 0.8229
> >> >
> >> > df_mod <- data.frame(val=as.character(),mod_result=as.character())
> >> >
> >> > res_multivariate <- rma.mv(yi=yi,
> >> > V=vi,
> >> > data=dat,
> >> > random = ~1 | Study/Article,
> >> > mods = ~ factor(Predictor)-1,
> >> > method = "REML"
> >> > )
> >> > summary(res_multivariate)
>
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