similar to: forest + igraph ?

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! I am working on some meta-analysis using the metafor package. I would like to extract values of the confidence intervals of the effect sizes of the single studies from an rma object. Those values are printed out when plotting a forest plot using the forest function on the rma object, however I was not able to locate them. Many thanks for your help! Jokel [[alternative HTML

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

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

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]]

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 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

Hello, I am performing a meta-analysis using the metafor package. My data are proportions and I used the Freeman Tukey double arcine (FT) transformation to fit the random effects model. Now I want to create a forest plot with my estimates backtransformed to the original scale of proportions. Can this be done? Regards, Patricia

Full_Name: Michael McStephen Version: 1.5.1 OS: Win2000 Submission from: (NULL) (203.25.148.63) When using read.table to read a data file section by section, I get an error that indicates R is attempting to read more "fields" than exist. The Data file looks like this: ---Start of file tmp.txt----------- Response Types = TPos TNeg FPos FNeg Anti Post MaxO Test ID,Username,Start

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

Hi all, Is there any grid search function to compute the maximum likelihood for a random variable? thanks, Samor --------------------------------- [[alternative HTML version deleted]]

Hello, Is there any test  for bimodality in R that x <- c(rnorm(1000,0,1),rnorm(1000,3,1)) hist(x,nclass=100) Thank you in advance for any help. Regards, Samor [[alternative HTML version deleted]]

Hello everybody, I am trying to install the library stepplr under windows (http://www.maths.bris.ac.uk/R/web/packages/stepPlr/index.html), in order to use the function plr, but I still have problem to find the right link for this purpose! I am very thankful for your help! Samor

Dear all, I am very thankful, if you could tell wheather it is possible to write paste("Mus., 10 ", expression(mu)," g", sep="") Thank you in advance, Samor --------------------------------- [[alternative HTML version deleted]]

I have some data in a CSV file: time,pos,t,tl 15:23:44:350,M1_01,4511,1127 15:23:44:350,M1_02,4514,1128 15:23:44:350,M1_03,4503,1125 ... 15:23:44:491,M2_01,4500,1125 15:23:44:491,M2_02,4496,1124 15:23:44:491,M2_03,4516,1129 ... 15:23:44:710,M3_01,4504,1126 15:23:44:710,M3_02,4516,1129 15:23:44:710,M3_03,4498,1124 ... Each pos (eg M1_01) is an independent time series. I would like to plot each

Hello, I recently started using the metafor package (version 1.6-0) in R (2.15.1, 64-bit Windows 7) and noticed that I was getting slightly different values when I manually calculated the standardized mean difference versus what escalc was giving me. Here''s a very simple example: escalc(measure="SMD", m1i=5,m2i=10,n1i=5,n2i=5,sd1i=1,sd2i=2,vtype="LS") The result

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