similar to: Using Metafor package: how to backtransform model coefficients when Freeman Tukey double arcine transformation is used

Dear All, I'm having trouble tweaking a forest plot made using the R meta-analysis package metafor. I did the analysis based upon the correlation coeff from studies and plotted the corresponding forest plot easily > q2<-rma(yi,vi,mods=cbind(grupo),data=qim) > q2 > forest (q2,transf=transf.ztor,digits=3, ... ,alim=c(0,1),refline=.5) > text(-1.55,42,"Esp?cie

Dear R community, I'm using the ,metafor'-package by Wolfgang Viechtbauer (Version: 0.5-5) to calculate random-effects meta-analyses using Correlations and Sample Sizes as the raw data. (By the way: Really a nice piece of work, Wolfgang! Thanks heaps.) I specified the "rma.uni' function so that it looks like this: MAergebnis<-rma.uni(ri=PosOutc, ni=N,

Hello all, I am using forest.rma to plot a random effects model meta-analysis. I noticed that refline sets a vertical line indicating the null hypothesis. Is there a way to draw another vertical line, possibly dashed, centered on the summary estimate? Prof. Viechtbauer, if you happen to read this, I'd like to thank you for making an excellent package. I have been using the metafor package

Hi Dr. Viechtbauer, I'm doing meta-analysis using your package 'metafor'. I used the 'IRFT' to transform the incident rate. But when I tried to back-transform the summary estimates from function rma, I don't know what's the appropriate ti to feed in function transf.iirft. I searched and found your post about using harmonic mean for ni to back-transform the double

Dear users of metafor, I am working on a meta-analysis using the metafor package. I have a excel csv database that I am working with. I am interested in pooling the effect measures for a particular subgroup (European women) in this csv database. I am conducting both sub-group and meta-regression. In subgroup-analyses, I have stratified the database to create a separate csv file just for European

I am using metafor to create forest plots. This code gives me the expected plot (setting x axis tick marks): forest(forest$OR, ci.lb=forest$Low, ci.ub=forest$High, at=log(c(.05, .25, 1, 10)), slab=forest$SNP, atransf=exp) As does this (setting colors): forest(forest$OR, ci.lb=forest$Low, ci.ub=forest$High, col=c(1,2,3), slab=forest$SNP, atransf=exp) But if I try to set both 'at' and

R-Experts: Does anyone know if there are R functions to perform the Freeman-Tukey double arcsine transformation and then backtransform it? Thanks, Brant Inman Mayo Clinic

Hi, I am a student using R for my final year project, with the metafor package being particularly helpful. I have been following the steps laid out in the manual 'Conducting Meta-analysis in R with the Metafor package' (Viechtbauer, 2010) and applying it to my own data of infected Anopheles mosquitoes across Africa. In particular, I am attempting to apply a mixed-effect model to my data

Hi everyone, I'm using the metafor package to meta-analyze a set of proportions. This is working really well for the raw proportions, but is there a way to back-transform the arcsine transformed proportions in the rma or forest functions with the atransf option? The estimates and CIs for the transformed proportions need to be back-transformed to be the sin of the estimate squared.

I have some question about metafor package. I'm interest to perform a random effect meta-analysis of proportion (single group summary of prevalence of disease in a population as reported by different study) It ask: 1. "PFT": The Freeman-Tukey double arcsine transformed proportion is reported to be equal to 1/2*(asin(sqrt(xi/(ni+1))) + asin(sqrt((xi+1)/(ni+1)))). Hovewer, i

Hello, Is it possible to have two meta-plots in one graph (not par(mfrow=c(2,1))? But somthing like  library(metafor)  library("igraph")    if (interactive()) {     forest(dat.Treat$RR, ci.lb=dat.Treat$lower, ci.ub=dat.Treat$upper, xlab="Relative Risk",slab=dat.Treat$ID,refline=1)     forest(dat.Control$RR, ci.lb=dat.Control$lower, ci.ub=dat.Control$upper, xlab="Relative

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

Dear metafor users, I am working on a meta-analysis of reliability and the correlation associations. I need some help about conducting categorical moderators variables. Questions 1: How to conduct the weighted ANOVAs assuming a mixed-effects model on the tranformed alpha coefficients/the tranformes correlation coefficients for the categorical moderator variables? Questions 2: How to

I would suggest to post this to the (recently created) R-sig-meta-analysis mailing list. See: https://stat.ethz.ch/mailman/listinfo/r-sig-meta-analysis Best, Wolfgang >-----Original Message----- >From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Naike Wang >Sent: Monday, June 26, 2017 08:32 >To: R-help at r-project.org >Subject: [R] Classic fail-safe N >

Hi - I am conducting a meta-analysis and I have a matrix of f-statistics, Ns and dfs from a series of studies that tested for an interaction in a 2x2 anova. I'd like to test whether the 2x2 interaction is significant in the aggregate. Similarly, I have a matrix of chi-square statistics that I'd like to meta-analyze. How can I input these test statistics into the "metafor"

Hello, I once used the metawin software to perform a meta-analysis (see metawinsoft, Rosenberg et al.) and produced normal qqplot to test for a potential bias in the dataset. I now want to re-use the same dataset with the package metafor by W. Viechtbauer (great package btw). I run the qqnorm.rma.uni function. I use standardized effect sizes as in metawin. QQplot generated with metafor differs

I had found the author's (Wolfgang Viechtbauer) earlier meta-analytic code in R, MiMa, useful. so I have been exploring metafor using an example dataset from MiMa. metafor provides a lot more. However, MiMa provided parameter estimates, standard errors, z values, etc. for individual moderators in the meta-analysis, but I don't see how to obtain these from metafor. Have you any help

Hello, I experimented the Metafor and Meta packages in the scope of replacing Excel for meta-analysis. I performed the first working example provided in Michael Borenstein's book "Introduction to Meta-Analysis" with Excel, Metafor and Meta. The numbers given by my spreadsheet, which I validated from Borenstein's book, conrespond quite closely to those given by Meta, but

A new package is now available via CRAN, called metafor. The metafor package consists of a collection of functions for conducting meta-analyses in R. Fixed- and random-effects models (with and without moderators) can be fitted via the general linear (mixed-effects) model. For 2x2 table data, the Mantel-Haenszel and Peto's method are also implemented. The package also provides various plot

Greetings, I wish to conduct a meta-analysis for which the outcome is a continuous variable measured on the same individuals before and after an intervention. Hence, the comparison is not made between two groups, but within groups, at diffrent times. Each study reports the mean outcome and SD before the intervention and the mean outcome and SD after the intervention. While p-values for