[R-meta] Metafor - regplot() for a categorical (and interaction) variable

Thanks for sharing the github package, Wolfgang. It looks like orchard_plot--similar to emmprep()--can't handle rank deficiencies which commonly occur in meta-analytic datasets due to various missing variable combinations. It also seems that orchard_plot is only designed for categorical variables and can't be used with quantitative/continuous variables.

I believe the issue that creates these limitations is that both emmprep() and orchard_plot() convert the rma objects to emmeans objects through emmeans::qdrg(). It might be possible to convert rma objects to one (I'm thinking lme::gls or something) that is readily acceptable in emmeans and likely both limitations may be lifted.

Reza


On Sat, Sep 7, 2024 at 8:15?AM Viechtbauer, Wolfgang (NP) <wolfgang.viechtbauer at maastrichtuniversity.nl> wrote:

Interesting alternative. Speaking of alternatives, the orchaRd package also provides some nice functionality along those lines:

library(metafor)

remotes::install_github("daniel1noble/orchaRd")
library(orchaRd)

dat <- escalc(measure="RR", ai=tpos, bi=tneg,
              ci=cpos, di=cneg, data=dat.bcg)

res <- rma(yi, vi, mods = ~ alloc, data=dat)

orchard_plot(res, mod="alloc", group="trial", xlab="log(Risk Ratio)")

Best,
Wolfgang

-----Original Message-----
From: Reza Norouzian <rnorouzian at gmail.com>
Sent: Saturday, September 7, 2024 14:40
To: R Special Interest Group for Meta-Analysis <r-sig-meta-analysis at r-
project.org>; lelid26 at gmail.com
Cc: Viechtbauer, Wolfgang (NP) <wolfgang.viechtbauer at maastrichtuniversity.nl>
Subject: Re: [R-meta] Metafor - regplot() for a categorical (and interaction)
variable

Emanuel,

Wolfgang's response is spot on. A shorter alternative might be to try the
following.

Reza

dat <- escalc(measure="RR", ai=tpos, bi=tneg,
              ci=cpos, di=cneg, data=dat.bcg)

res <- rma(yi, vi, mods = ~ alloc, data=dat)

grd <- emmprep(res) # check out metafor's documentation

emmeans::emmip(grd, ~alloc, CIs=TRUE)  # check out emmeans' documentation

On Sat, Sep 7, 2024 at 7:04?AM Viechtbauer, Wolfgang (NP) via R-sig-meta-
analysis <mailto:r-sig-meta-analysis at r-project.org> wrote:
This is one issue. However, there are more issues at hand here, since
regplot(res, mod = ~ Continent) isn't gong to work either, as this will trigger
the error "Can only specify a single variable via argument 'mod'." The reason is
that the 'mod' argument is not meant to take a formula as input. However, when
you do, then the length of 'mod' will be 2 (length(~ blah)), which triggers the
error.

@Emanuel: While I don't know what you really intend to do here, I suspect you
would like to show all levels of 'Continent' on the x-axis. This is not so
easily accomplished with the regplot() function, which is designed for
visualizing quantitative/continuous moderators. For example:

dat <- escalc(measure="RR", ai=tpos, bi=tneg,
                            ci=cpos, di=cneg, data=dat.bcg)

res <- rma(yi, vi, mods = ~ ablat, data=dat)
res

regplot(res, mod="ablat")

A dichotomous moderator is also easily handled:

dat$random <- ifelse(dat$alloc == "random", 1, 0)

res <- rma(yi, vi, mods = ~ random, data=dat)
res

regplot(res, mod="random")

We might want to make this look a bit nicer, maybe like this:

regplot(res, mod="random", xlab="Method of Treatment Allocation", xaxt="n")
axis(side=1, at=c(0,1), labels=c("Non-Random", "Random"))

However, things become more tricky with a factor variable that has 3 or more
levels:

res <- rma(yi, vi, mods = ~ alloc, data=dat)
res

regplot(res, mod="alloc")

This will not work, since there are two 'alloc' dummy variables, but regplot()
is designed to place a single variable on the x-axis. One could do:

par(mfrow=c(2,1))
regplot(res, mod="allocrandom")
regplot(res, mod="allocsystematic")
par(mfrow=c(1,1))

but this is showing the difference between random and not random (consisting of
'systematic' and 'alternate') in the first plot and the difference between
systematic and not systematic (consisting of 'random' and 'alternate') in the
second plot. Probably not how most people would want to visualize this. Instead,
I suspect most would want to show three 'columns' of points, corresponding to
the three levels, with lines connecting the fitted/predicted values for these
levels.

I had not quite considered that some may want to do something like this with
this function. I am not sure how easy it would be to add this kind of
functionality directly to regplot() given some of the internal intricacies.
However, with a small trick, we can still accomplish this. A model with a
categorical moderator with p levels can be represented as a polynomial
regression model to the degree p-1 where the first term is the linear one (which
we want to place on the x-axis). This, combined with the possibility to pass
predicted values to regplot() via the 'pred' argument, we can place all levels
on the x-axis as follows:

dat$anum <- as.numeric(factor(dat$alloc))
res <- rma(yi, vi, mods = ~ poly(anum, degree=2, raw=TRUE), data=dat)
res

pred <- predict(res, newmods=unname(poly(1:3, degree=2, raw=TRUE)))
pred

regplot(res, mod=2, pred=pred, xvals=c(1:3), xlim=c(1,3), xlab="Allocation
Method", xaxt="n")
axis(side=1, at=1:3, labels=levels(factor(dat$alloc)))

Best,
Wolfgang

-----Original Message-----
From: R-sig-meta-analysis <mailto:r-sig-meta-analysis-bounces at r-project.org>

On Behalf

Of Michael Dewey via R-sig-meta-analysis
Sent: Friday, September 6, 2024 11:04
To: R Special Interest Group for Meta-Analysis <r-sig-meta-analysis at r-
http://project.org>
Cc: Michael Dewey <mailto:lists at dewey.myzen.co.uk>
Subject: Re: [R-meta] Metafor - regplot() for a categorical (and interaction)
variable

Dear Emanuel

I think you will find that the parameter is named mods in rma.uni but
mod in regplot.

Michael

On 06/09/2024 00:56, Emanuel Schembri via R-sig-meta-analysis wrote:

Hi

I am trying to plot a bubble plot using the replot() function in
Metafor. However, I cannot make it work for a categorical moderator
(and an interaction between a categorical and numerical variable),
while it does work when inputting a numerical or date.

Any help would be greatly appreciated.

Regards,

Emanuel

res <- rma(yi, vi, mods = ~ Continent, data= df)
regplot(res, mods = ~ Continent)

Mixed-Effects Model (k = 24; tau^2 estimator: REML)

tau^2 (estimated amount of residual heterogeneity):     3.5128 (SE = 1.1529)
tau (square root of estimated tau^2 value):             1.8743
I^2 (residual heterogeneity / unaccounted variability): 99.79%
H^2 (unaccounted variability / sampling variability):   477.76
R^2 (amount of heterogeneity accounted for):            8.05%

Test for Residual Heterogeneity:
QE(df = 21) = 1150.4471, p-val < .0001

Test of Moderators (coefficients 2:3):
QM(df = 2) = 5.7609, p-val = 0.0561

Model Results:

                    estimate      se    zval    pval    http://ci.lb   ci.ub
intrcpt              2.2738  1.3346  1.7037  0.0884  -0.3420  4.8897  .
ContinentAsia      4.3152  1.8165  2.3756  0.0175   0.7549  7.8755  *
ContinentEurope    2.6747  1.4053  1.9032  0.0570  -0.0797  5.4291  .

---
Signif. codes:  0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1

regplot(res, mods = ~ Continent)

Error in regplot.rma(res, mods = ~Continent) :

   Must specify 'mod' argument for models with multiple predictors.