I am working on a meta analysis using the metafor package. I want to calculate the effect size in using the package but am running into some trouble. I am trying to calculate effect size using the escalc function. I have a file with values ~200 rows containing data on the control/test means variances, and sample numbers. For each row I would like to calculate the effect size. I would now like to use the escalc function to determiner the effect size using SMD.
My current code is as follows:
# escalc function
escalc <- function(measure, ai, bi, ci, di, n1i, n2i, x1i, x2i, t1i, t2i, m1i, m2i, sd1i, sd2i, xi, mi, ri, ti, sdi, r2i, ni, yi, vi, sei,
data, slab, subset, include, add=1/2, to="only0", drop00=FALSE, vtype="LS", var.names=c("yi","vi"), add.measure=FALSE, append=TRUE, replace=TRUE, digits, ...)
# apply data and add effect size col to data frame
data$ES <- escalc(measure = SMD, dat$MRE1, dat$MTE2, dat$VRE1, dat$VTE2, dat$NR1, dat$NR2, data = dat)When I run this code once there seems to be no problem/error (if I run the code more than once it says "Error: C stack usage 15925888 is too close to the limit" - unsure what this means) but my dataframe does not have a new column with the ES for each study. When I highlight the new variable and click enter (to see what the data looks like) it says NULL so I don't think it actually ran. How can I get a summary of the effect sizes?
I am unsure what I am doing wrong or how to see what the effect sizes I've calculated are. I've been reading the metafor documentation and am unsure what I am doing wrong (). Do I need to calculate escalc for each paper? Any help is greatly appreciated.
Thank you!
1 Answer
You should use:
dat <- escalc(measure="SMD", m1i=MRE1, m2i=MTE2, sd1i=sqrt(VRE1), sd2i=sqrt(VTE2), n1i=NR1, n2i=NR2, data=dat)Note that the SDs are the input for arguments sd1i and sd2i, so if you have the variances, we need to take the square-root of them.
