I was conducting a meta-analysis of single proportions(i.e. without a control group) using the metafor package. When I performed a classic fail-safe N, I noticed that the result (the number of missing studies that would bring p-value to the alpha, to be exact)was different than that I got in Comprehensive Meta-Analysis Version 2.0. I wonder why R and CMA got different results.
Below is the R code:
dat=read.table("Your working directory\\Example.csv",header=T,sep=",")
transf.ies=escalc(xi=cases,ni=total,measure="PLO",data=dat) #I transform the data using the logit transformation first. In CMA, it also uses the logit transformation.
transf.pes=rma(yi,vi,data=transf.ies,method="DL",weighted=TRUE) #Pooling individual effect sizes in the logit scale.
fsn(yi,vi,data=ies.ft,type="Rosenthal")#Performing the fail-safe N.
Below are the results from R:
Fail-safe N Calculation Using the Rosenthal Approach
Observed Significance Level: alpha 5931.00000
Notice that I got 8446 in R and 5931 in CMA. Can anyone shed some light on this discrepancy? Thank you!
You can find my data set here: https://drive.google.com/open?id=0B41wTxciaMqtTEJWZE9sX20wOXM