# [R-meta] proportional meta-analysis

Ahmed Tarek tbedair.ahmed at gmail.com
Sun Feb 4 18:55:42 CET 2018

```Dear all,

I am quite the beginner when it comes to R. I have recently started to do a meta-analysis investigating the retention of different dental fissure sealers. The dataset included: study name, length of study (2,3,5, years), total number of teeth initially sealed, number of teeth sealed at the end of study, material used for this study.

I divided data according to follow up, and made a proportional meta analysis forest plot comparing the different materials after 2 years (another plot for 3 yr, and another for 5). I made the proportional meta analysis based on the Random effects model using the package “meta”.

1. If material X was worse than material Y, can I show that the difference was statistically significant? (considering I was comparing 5 different materials at the same time)

2. I noticed the heterogeneity results (I^2) to be higher for a certain material even though on the forest plot, the results did not seem that heterogeneous when compared to other groups that reported lower heterogeneity. Is that ok? also the study weights did not necessarily represent study sample size, would that be because I used the DL method?

######CALCULATE OVERALL SUMMARY PROPORTION#######
ies.logit=escalc(xi=cases, ni=total, measure="PLO", data=dat)
pes.logit=rma(yi,vi,data = ies.logit, method = "DL", weighted = TRUE)
pes=predict(pes.logit, transf = transf.ilogit, digits = 5)
print(pes,digits=5); print(pes.logit,digits=4);confint(pes.logit,digits = 2)
#####CALCULATE SUBGROUP ACCORDING TO MATERIAL#######
pes.logit.Auto=rma(yi,vi,data=ies.logit,subset=material=="Auto",method = "DL")
pes.logit.Light=rma(yi,vi,data=ies.logit,subset=material=="BLight",method = "DL")
pes.logit.F=rma(yi,vi,data=ies.logit,subset=material=="F",method = "DL")
pes.logit.GI=rma(yi,vi,data=ies.logit,subset=material=="GI",method = "DL")

pes.Auto=predict(pes.logit.Auto, transf=transf.ilogit, digits = 5)
pes.Light=predict(pes.logit.Light, transf=transf.ilogit, digits = 5)
pes.F=predict(pes.logit.F, transf=transf.ilogit, digits = 5)
pes.GI=predict(pes.logit.GI, transf=transf.ilogit, digits = 5)

3. For the 2 year studies, almost 100 studies were included, making the forest plot look a bit crammed, should I use another package, that could make it look better?

4. I also could not arrange the materials the way I wanted in the forest plot, they kept being arranged alphabetically, even though I used the command “sort=FALSE”

I really appreciate the help.

Regards,
Ahmed Bedir
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