-----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
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.