[R-meta] OR using metafor: Standard group with many zeros

[Nelson Ndegwa]

Hi,

I am interested in calculating an OR for a developing some outcome after
new-treatment compared to standard treatment. I have proportions data, with
19 studies.

I ran a Random-Effects Model (code below, data attached) with the model
type: Unconditional Model with Random Study Effects as follows, then
exponentiated the coefficient for an OR:


Two questions:


   1. I noticed there were quite a few zeros in the standard group (about
   8/19 studies) . This is sometimes because there were no standard patients
   in that study. 0 patients and 0 events. Should it be a zero or a . for
   missing instead? what is the best way to handle this situation? I tested
   running above code by using both TRUE or FALSE in the drop00 option, but
   the results didn't change.
   2. I got results but also this message which am not sure what it means
   for the results I have got, are they still valid? "*Currently not
   possible to fit RE/ME model='UM.RS <http://UM.RS>' with nAGQ > 1. nAGQ
   automatically set to 1.Model failed to converge with max|grad| = 0.00207718
   (tol = 0.001, component 1)*"

I shall greatly appreciate your comments/advice.

=========
CODE RUN
=========
res1 <- rma.glmm(measure="OR", ai=treatment_events, n1i=treatment_total,
ci=control_events, n2i=control_total, data=repdat, model="UM.RS")

print(res1, digits=3)

predict(res1, transf=exp, digits=2)

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