Hi all, 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. ranktest(transf.pes) #Performing the fail-safe N. *Below are the results from R:* Fail-safe N Calculation Using the Rosenthal Approach Observed Significance Level: <.0001 Target Significance Level: 0.05 Fail-safe N: 8446 *Below are the Classic fail-safe N results from CMA:* Z-value for observed studies 19.91594 P-value for observed studies 0.00000 Alpha 0.05000 Tails 2.00000 Z for alpha 1.95996 Number of observed studies 58.00000 Number of missing studies that would bring p-value to > 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 Best, Naike [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.