similar to: Help: Meta-analysis with metacor

Hi All, I have conducted a meta analysis using the metabin function. I want to plot 5 subgroups on the same forest plot. I have managed to do this using the byvar argument but when i plot the forest plot in R graphics I am unable to view the very top and very bottom of the image. It is as though the plot is too long. Is there a way in which I can ask R to show the entire plot within the

Version 2.0-0 of meta (an R package for meta-analysis) is now available on CRAN. Changes are described below. Yours, Guido Major revision R package meta linked to R package metafor by Wolfgang Viechtbauer to provide additional statistical methods, e.g. meta-regression and other estimates for tau-squared (REML, ...) New functions: - metareg (meta-regression) - metabias

Version 2.0-0 of meta (an R package for meta-analysis) is now available on CRAN. Changes are described below. Yours, Guido Major revision R package meta linked to R package metafor by Wolfgang Viechtbauer to provide additional statistical methods, e.g. meta-regression and other estimates for tau-squared (REML, ...) New functions: - metareg (meta-regression) - metabias

Is there a way to prevent browselists from machines other than those of my choosing to show up in the browselists/network neighbourhood? I don't want win95 clients that offer shares themselves to show up in the network neighbourhood. Michel. -- Michel van der Laan - michel@nijenrode.nl http://www.nijenrode.nl/~michel

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Dear all, I would like to fit a linear regression with replication (on each year, observation is replicated, e.g 4 times). The independent variable ranges for instance 1-5 year, so I expect to have a linear fit of 5 points. For that purpose I do these (with dummy variables x and y): x<-rep(seq(1:5),4) y<-rnorm(20) linreg<-lm(y~x) fitted.values(linreg) # why produce 20 points of

I have a simple table of data: Result Var1 Var2 Var3 1 0.10 0.78 0.12 0.38 2 0.20 0.66 0.39 0.12 3 0.10 0.83 0.09 0.52 4 0.15 0.41 0.63 0.95 5 0.60 0.88 0.91 0.86 6 -0.02 0.14 0.69 0.94 I am trying to achieve two things: 1) Manipulate this data so that I have the "Result" data unchanged, and all the other data

Hi, I wonder if it is possible to create an DLL or EXE file performing R procedures. Instead of running R, reading data and calling some procedures, I would like to use R functions in the following way: "C:\linearRegression.exe data.txt" which would produce let's say file "output.txt" with the results. Is there some way how to do it? Thanks a lot. Pavel Vanecek

----- Original Message ----- From: allan d. go To: blue@bluepoint.com.ph Sent: Tuesday, October 29, 2002 8:54 PM Subject: Samba PDC guys, i'm configuring a Samba Primary Domain Controller. i compiled the 2.2.5 version with ./configure --prefix=/usr/samba --with-quotas and followed the Samba-HOWTO-Collection I configured my Win2K workstation with the following parameters:

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 want to use the grplasso package on a data set where I want to fit a linear model.? My interest is in identifying significant?beta coefficients.? The documentation is a bit cryptic so I'd appreciate some help. ? I know this is a strategy for large numbers of variables but consider a simple case for pedagogical puposes.? Say I have?two 3 category predictors (2 dummies each), a binary

Hi Group, I performed the following commands to build my package in R 2.0 under Windows XP I got all my tools from Dr. Duncan Mudroch's website. I did a RCMD build dnal and it built a tar file for me. I did a RCMD INSTALL dnal and it installed well. When i do RCMD check dnal i get the following 2 WARNINGS with no Errors. checking package directories..WARNING Subdirectory 'src'

Dear all, We have got data (response and predictor variables) for each country of the world; I started by fitting standard GLM and tested for spatial correlation using variogram models (geoR) fitted to the residuals of the GLM. Spatial autocorrelation is significant. Therefore, I think about using general estimation equations (geeglm or geese in geepack) allowing for residual spatial

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 all I am analyzing a data set containing information about the behaviour of marine molluscs on a vertical wall. Since I have replicate observations on the same individuals I was thinking to use the geepack library. The data are organised in a dataframe with the following variables Date = date of sampling, Size = dimensions (mm) Activity duration of activity (min) Water = duration of

I have included data at the bottom of this email. It can be read in by highlighting the data and then using this command: dat <- read.table("clipboard", header = TRUE,sep="\t") I can obtain solutions with both of these: library(gee) fit.gee<-gee(score ~ chem + time, id=id, family=gaussian,corstr="exchangeable",data=dat) and library(yags) fit.yags <-

Okay, spending the time to dot t's and cross i's (or something like that), I think I have something now that can be called 3.00-worthy, so let's call it a release candidate. Changes over the earlier 3.00 prereleases: - -m and -a options now supported by the DOS installer. - PXELINUX now allows IP addresses, FQDNs, and truncated hostnames when specifying an alternate TFTP server

Hello All, I have posted to this list before regarding the same issue so I apologize for the multiple e-mails. I am still struggling with this issue so I thought I'd give it another try. This time I have included reproducible code and a subset of the data I am analyzing. I am running an ANOVA with three factors: GROUP (5 levels), FEATURE (2 levels), and PATIENT (2 levels), where

Dear R experts I am running a negative-binomial GLM (glm.nb) to test the null hypotheses that species 1 and 2 are equally abundant between site 1 and site2, and between each other. So, I have a 2x2 factorial design with factors Site (1,2) and Taxon (1,2). Since the Site:Taxon interaction is significant, I need to do the equivalent to a "post-hoc test" for ANOVA, however, the same tests

Hi, I would consider the calculation of r-squared in the following to be a bug, but then, I've been wrong before. It seems that R looks to see if the model contains an intercept term, and if it does not, computes r-squared in a way I don't understand. To my mind, the following are two alternative parametrizations of the same model, and should yield the same r-squared. Any insight much