[R-meta] Using control-only and treatment-only studies in 'metafor' -- can you calculate effect sizes with NAs in your table?

[Viechtbauer, Wolfgang (SP)]

Dear Veronica,

Measure 'SMD' is for computing the standardized mean difference between two groups. It does not seem applicable to your data.

Can you describe in a bit more detail what these "mean accuracy scores" are? How are they computed within an individual study?

Best,
Wolfgang

-----Original Message-----
From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org] On Behalf Of Veronica Frans
Sent: Tuesday, 30 October, 2018 18:29
To: r-sig-meta-analysis using r-project.org
Subject: [R-meta] Using control-only and treatment-only studies in 'metafor' -- can you calculate effect sizes with NAs in your table?

Dear forum,

I would like to use the 'metafor' package for my meta-analysis. I am
comparing the results (mean accuracy score from 0  to 1) of articles that
use one procedure (the 'treatment'; group 1) versus those that don't (the
'control'; group 2). However, all of my studies present results for only
the treatment or only the control, but never both.

To run the escalc() function (measure=SMD), is it possible to have studies
with NA's in m1i, sd1i, n1i, and vice-versa?

Unfortunately, when I use my table in R, the escalc() function gives me
NA's for yi and vi.

Here's an example of the code I used:

mod.means <-data.frame(
                study = c("UID6","UID7","UID11","UID13","UID17","UID18"),
                n1i = c(1,1,16,NA,NA,21), #number in treatment
                n2i = c(NA,NA,NA,2,2,NA), #number in control
                m1i = c(.931,.81,.977,NA,NA,.878), #treatment means
                m2i = c(NA,NA,NA,.865,.69,NA),     #control means
                sd1i = c(0,0,.012,NA,NA,.0386),  #treatment sd
                sd2i = c(NA,NA,NA,.05,.03,NA),   #control sd
                scale = c(3,4,1,1,3,2)           #potential moderator
                )

all.meta <- escalc(measure = "SMD",
                   m1i = m1i, m2i=m2i,     #means
                   sd1i=sd1i, sd2i = sd2i,  #standard deviation
                   n1i=n1i, n2i = n2i,         #numbers
                   data = mod.means)

all.meta  #show table

Perhaps I should format my table in a different way or consider a different
meta-analysis approach other than "SMD"?

Any advice on this is greatly appreciated. Thank you for your time!

Sincerely,

Veronica Frans