similar to: Extract confidence intervals from rma object (metafor package)

Dear R-experts, The forest.rma() function from the metafor package creates nice forest plots for presenting the results of a meta-analysis. These plots can be annotated for e.g. giving names to the columns. E.g. as in the documentation of the package: data(dat.bcg) ### meta-analysis of the log relative risks using a random-effects model res <- rma(ai=tpos, bi=tneg, ci=cpos, di=cneg,

Dear R-experts! In a meta-analysis (metafor) I would like to assess the effect of two categorical covariates (A & B) whereas they both have 4 levels. Is my understanding correct that this would require to dummy-code (0,1) each level of each covariate (A & B)? However I am interested in the main-effects and the interaction of these two covariates and the dummy-coding would only allow to

Dear R-community, I'm currently trying to assemble a forest plot using the "forest" function from package "metaphor". Works well. Even the regular "main"-argument works for adding a title to the graph. However, I would like to add one top row which explains the nature of the columns. Very much like the usual header in spreadsheet programs. For example:

Hi I have tryed to do the meta-regression in metafor package, but I would like to get the standardized coefficients for each variable, however in command:   Ø  res<-rma.uni (yi, vi, method="REML", mods=~cota+DL+uso+gadiente+idade, data= turbidez)   I just have the coefficients no standardized (estimate) of the multiple regression. What I need to do? Thanks Fernanda Melo

Dear R User, Please, I am new to R. I want to overlay density plot for predictive interval pooled result in meta-analysis. http://addictedtor.free.fr/graphiques/graphcode.php?graph=114 Regards Frank Peter

Hello metafor users, I'm using metafor to perform a single-effect summary estimate of the raw proportion of patients experiencing a post-operative complication, and I'm interested in seeing if this proportion differs between the three most commonly used surgical techniques. The software is working as expected, but I would like to double check on the interpretation of my mixed-effect model

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

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

Dear All, As an attempt to highlight the overall pattern in a Forest plot, I would like to "highlight" the area around HR=1. I cannot find any simple tools for painting a grey ribbon between 0.9 and 1.1. Any suggestions? Thank you in advance! Cheers, Patrik [[alternative HTML version deleted]]

Dear R-experts! Running a meta-analysis (using the magnificent metafor-package), I use cohen's d as a main outcome measure in a random-effects model. For most of the samples cohen's d is derived form a comparison of two groups (A & B). However some studies report results from an ANOVA (one-factor with three levels: C,D,E) whereas two groups (C,D) correspond to one group in the other

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,

Hi, I have been looking for an R package which allowed to do meta-analysis (both pairwise and network/mixed-treatment) at arm-level rather than at trial-level, the latter being the common way in which meta-analysis is done. By arm-level meta-analysis I mean one that accounts for data provided at the level of the individual arms of each trial and that does not simply derive the difference between

Dear R users, In metafor 1.6-0, the Mantel-Haenszel method is implemented by the rma.mh() function. I have observed that the sum of the weights computed by weights(x) doesn't add to 100% when x is an object of class rma.mh. The consequences of this fact can be clearly seen when a forest diagram is drawn with forest(x), which calls weights(x) (or more precisely, the method weights.rma.mh()

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

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

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

Dear all, I'm currently applying a mixed model approach to meta analysis using the package metafor. I use the "model.matrix()" function to create dummy variables. The option btt gives me the combined test for the dummies. Problem is, I don't know which indices I have to use, and can't really figure it out from the help file and the examples. I use following code : X <-

Hello. A quick question about incorporating variation due to study in the metafor package. I'm working with a particular data set for meta-analysis where some studies have multiple measurements. Others do not. So, let's say the effect I'm looking at is response to two different kinds of drug treatment - let's call their effect sizes T1 and T2. Some studies have multiple

Hi, I would like to do a meta-analysis, i.e., a mixed-effects regression, but I don't seem to get what I want using both the nlme or metafor packages. My question: is there indeed no way to do it? And if so, is there another package I could use? Here are the details: In my meta-analysis I'm comparing different studies that report a measure at time zero and after a certain followup

I'm puzzled by the behaviour of factors in rma models, see example and comments below. I'm sure there's a simple explanation but can't see it... Thanks for any input John Hodgson ------------------------------------- code/selected output ----------------- library(metafor) ## Set up data (from Lenters et al A Meta-analysis of Asbestos and Lung Cancer... ##