# [R-meta] "Categorical" moderator varying within and between studies

James Pustejovsky jepu@to @end|ng |rom gm@||@com
Wed Jun 3 05:00:36 CEST 2020

```Hi Simon,

The same strategy can be followed by using dummy variables for each unique
level of a categorical moderator. The idea would be to 1) create dummy
variables for each category, 2) calculate the study-level means of the
dummy variables (between-cluster predictors), and 3) calculate the
group-mean centered dummy variables (within-cluster predictors). Just like
if you're working with regular categorical predictors, you'll have to pick
one reference level to omit when using these sets of predictors.

Here is an example of how to carry out such calculations in R, using the
fastDummies package along with a bit of dplyr:

library(dplyr)
library(fastDummies)
library(robumeta)

data("oswald2013")

oswald_centered <-
oswald2013 %>%

# make dummy variables
mutate(
Scoring = recode(Scoring, "Difference Score" = "Difference", "Relative
Rating" = "Relative")
) %>%
dummy_columns(select_columns = "Scoring") %>%

# centering by study
group_by(Study) %>%
mutate_at(vars(starts_with("Scoring_")),
list(wthn = ~ . - mean(.), btw = ~ mean(.))) %>%

# calculate Fisher Z and variance
mutate(
Z = atanh(R),
V = 1 / (N - 3)
)

# Use the predictors in a meta-regression model
# with Scoring = Absolute as the omitted category

robu(Z ~ Scoring_Difference_wthn + Scoring_Relative_wthn +
Scoring_Difference_btw + Scoring_Relative_btw, data = oswald_centered,
studynum = Study, var.eff.size = V)

Kind Regards,
James

On Tue, Jun 2, 2020 at 6:49 PM Simon Harmel <sim.harmel using gmail.com> wrote:

> Hi All,
>
> <
> https://cran.r-project.org/web/packages/robumeta/vignettes/robumetaVignette.pdf
> >*
>  (*top of the page*) recommends that if a *continuous moderator *varies
> both within and across studies in a meta-analysis, a strategy is to break
> that moderator down into two moderators by:
>
> *(a)* taking the mean of each study (between-cluster effect),
>
> *(b)* centering the predictor within each study (within-cluster effect).
>
> BUT what if my original moderator that varies both within and across
> studies is a *"categorical" *moderator?
>
> I appreciate an R demonstration of the strategy recommended.
> Thanks,
> Simon
>
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>
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```