similar to: Metafor package

I have the same problem of a previous request HOW to use the survivalROC (or another library in R) to get optimal cut-off values? I want to use the time-dependent survivalROC package.according to the,reference material,it only gives a partial set of ordered cut-off values .eg. -------------------------------------------------------------------------------- data(mayo) str(mayo) attach(mayo)

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I have the same problem of a prevous request HOW to use the survivalROC (or another library in R) to get optimal cut-off values? I want to use the time-dependent survivalROC package.according to the,reference material,it only gives a set of ordered cut-off values .eg. -------------------------------------------------------------------------------- data(mayo) str(mayo) attach(mayo)

Dear all, I use R 2.14.2 for Windows XP I have no problem with R Commander version 1.7-2, but now I have a problem with R Commander (Rcmdr) version 1.8-3. After I lunch R Commander (sdi as well standard) if I try to import data (i. from Stata datafile) I have this Warning message: Error in structure(.External("dotTclObjv", objv, PACKAGE = "tcltk"), class =

Subject: Re: [R] Problems with R Commander version 1.8-3 Many thanks for your kindly replay. I just use a At this time I use an earlier version of the package. I try to install the Rcmdr from R-Forge. Many tanks again Message: 21 Date: Wed, 28 Mar 2012 08:04:09 -0400 From: "John Fox" <jfox at mcmaster.ca> To: <petretta at unina.it> Cc: r-help at r-project.org

Dear all, I am interested to evaluate reclassification using net reclassification improvement and Integrated Discrimination Index IDI after survival analysis (Cox proportional hazards using stcox). I search a R package or a R code that specifically addresses the categorical NRI for time-to-event data in the presence of censored observation and, if possible, at different follow-up time points. I

Dear all I generated predicted risk of death for each subject in the study by means of Cox proportional hazards model at 8 year of follow-up, a time point at which follow-up was more than 90% complete. It is possible to extrapolate to 10-year the predicted risk of each subjet by assuming an exponential distribution? Any help would be greatly appreciated. Thanks for your consideration.

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

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.

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 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 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

Good morning to everybody, I have a problem : how can I import excel files in R??? thank you very much Dr.sa. Erika Frigo Università degli Studi di Milano Facoltà di Medicina Veterinaria Dipartimento di Scienze e Tecnologie Veterinarie per la Sicurezza Alimentare (VSA) Via Grasselli, 7 20137 Milano Tel. 02/50318515 Fax 02/50318501 [[alternative HTML version deleted]]

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

Dear Metafor users, I''d like to test a model with 2 continuous and 2 categorical moderators in a meta regression. One categorical parameter has 2 levels and the other has 4 levels. If I understand correctly, when I include all moderators in the model, Metafor returns main effects of the continuous parameters and contrasts of each level of categorical moderators with the intercept (which

Dear Metafor users, I'm conducting a metaanalysis of prevalence of a particular behaviour based on someone elses' code. I've been labouring under the impression that this: summary(rma.1<-rma(yi,vi,mods=cbind(approxmeanage,interviewmethodcode),data=mal,method="DL",knha=F,weighted=F,intercept=T)) is doing the multivariate analysis that i want, but have read that