similar to: Major update: meta version 2.0-0

Hello, I am writing a meta-analysis on the complication and reoperation rates after 5 treatment modalities of a distal radius fracture. I have a code to compare the complication and reoperation rates. Currently it is using a mixed effects model. Is it possible to change the code so a random effects model is used? Thank you very much, Jay R code library(meta) library(readxl) All <-

I cannot seem to get a L'abbe plot to work on R. I do not understand what the X coordinates, or alternatively an object of class metabin, is supposed to mean. What is a class of metabin? Institute of Behavioral Genetics University of Colorado, Boulder Whitney.Melroy at Colorado.EDU

The code in your mail in a mangled mess, since you posted in HTML. Please configure your email client to send emails in plain text. Could you explain what exactly you mean by "Currently it is using a mixed effects model. Is it possible to change the code so a random effects model is used?" Best, Wolfgang >-----Original Message----- >From: R-help [mailto:r-help-bounces at

Dear R-Community, I'm currently trying to find a way to conduct a meta-analysis in R. I would like to analyze data from mostly-cross-sectional survey-studies. The effect sizes would be correlations. The R packages "meta" and "rmeta" are, as far as I can see, set up for analysis with effect sizes for differences (i.e. comparison of the means/odds-ratios of experimental

R-experts: In 2002, Hans Van Houwelingen et al. published a tutorial on how to do meta-regression in Statistics in Medicine. They used the classic BCG dataset of Colditz to demonstrate correct methodology and computed the results using PROC MIXED in SAS. In trying to duplicate the results presented in this paper, I have discovered that I can reproduce certain items with lmer but not

Hi, I want to do a meta-analysis with count data for treatement/control cases. Mi problem is that I need to use zero values (an informative zero value) for the mean and standard deviation for one of the treatement, but R has a problem: "Studies with zero values for sd.e or sd.c get no weight in meta-analysis". I can agroup the case by Family (byvar=Family). ¿Can you help me? Thanks!

Estimado Gracias por su ayuda José 2023-05-06 19:47 GMT-04:00, Carlos Ortega <cof en qualityexcellence.es>: > Hola, > > Si añades lo que destaco, defines el layout y queda más ajustado en la > pantalla. > > #-------------------------- > library(readxl) > Sistolica <- read_excel("./Sistolica1.xlsx") > library(meta) > m <- metacont( >

Hi! I want to do a meta-analysis with count data for treatement/control cases. Mi problem is that I need to use zero values (an informative value) for the mean and standard deviation for one of the treatement, but R has a problem: "Studies with zero values for sd.e or sd.c get no weight in meta-analysis". I can agroup the case by Family (byvar=Family). ¿anybody help me? Thanks! >

Dear Sir or Madam, I am trying to plot forest plot. I extracted odds ratio and their corresponding 95% confidence interval from papers, then I calculated the log(OR) and standard error using the following command OR<-metagen(logOR,selogOR,sm="OR") forest(OR,comb.fixed=TRUE,comb.random=TRUE,digits=2) However, it does not produce a forest plot. Can someone kindly help? Thank

Trying to do a meta-analysis of correlations in R using the meta package; have tried several things and keep getting a similar error. Can anyone help explain the error? > cor<-c(-0.3018, 0.667, -3.8002, -0.607, -0.4885, -3.8002, -0.0701, 0.1348, -0.9505, -0.5709, -0.6127, -1.2419, -0.1511, -0.1054)> n<-c(3,4,3,3,3,3,16,36,30,9,3,3,30,4)> library(meta)> metacor(cor, n, data=NULL,

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

Hi I'm conducing a meta-analysis using the meta package. Here's a bit of code that works fine - tmp <- metacont(samplesize.2, pctdropout.2, sddropout.2, samplesize.1, pctdropout.1, sddropout.1, data=Dataset, sm="WMD") I would now like to control for a couple of variables (continuous and categorical) that aren't in the equation. Is meta

Hi, ? Is there some easy way to split the grid.newpage() into two columns? For example, how could I put the two forest plots below (meta1 and meta2) next to each other? library(meta) data(Olkin95) meta1 <- metabin(event.e, n.e, event.c, n.c,data=Olkin95, subset=c(41,47,51,59),sm="RR", meth="I",studlab=author) meta2=meta1 meta2$studlab=rep("",length(meta1$studlab)

Stefan Roepcke <stefan.roepcke at metagen.de> writes: > Hey, > > hopefully there is an easy way to solve my problem. > All that i think off is lengthy and clumsy. > > Given a data.frame d with columns VALUE, FAC1, FAC2, FAC3. > Let FAC1 be something like experiment number, > so that there are exactly the same number of rows for each level of FAC1 > in the

Hello! I have some data stored into 2 separate csv file. 1 file (called A.csv) (12 results named Group1, Group2, Group3, etc...) odds ratios, 2 file (called B.csv) 12 corresponded errors. How to import that data into R and make forest plot like I saw inside help file Rmeta and meta with included different font colors and names trough X and Y axis. I know for meta libb ... out <-

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

Hi All, I have run a series of random effects meta regressions on binomial outcomes using the metabin function in R. Now I would like to conduct some random effects meta regressions on the outcomes. Is there a command available which will allow for me to test the impact of a certain variable on the relative treatment effect from my meta regressions? Many Thanks, Steph -- View this message in

Hi, I am trying to add additional columns to a forest plot using the meta package. The study information and subgroup analysis plotting is handled properly. For this output the data is ordered first by subgroup label (rnd.subgroup1 in the example) and second decreasing size of totals ('n' in the example). The proper ordering of this data is confirmed by the color coding (black and red in

OK - I've been doing some work on getting a forest plot or two together for a sub-group analaysis. Thats the crucial thing - because its a sub-group analysis rather than a meta-analsysis and all the forest (meta) and forestplot (rmeta) instructions assume you are doing a meta-analysis. I found rmeta didn't play nicely for me so I'm using the meta package with forest. Here's some

Estimados Como logro en el forest plot que el gráfico quede en unos margenes que se pueda ver completo. Adjunto archivo saludos José library(readxl) Sistolica <- read_excel("000 EN DISEñO/0000 eli cardio 2/0000 para metanalisis/Sistolica.xlsx") library(meta m <- metacont(Ne, Me, Se, Nc, Mc, Sc, studlab=paste(Author, year), forest(m) funnel(m) ------------ próxima