similar to: meta.summaries and se's of effect sizes

I would like to combine time-series data to test for correlations and interactions using random and fixed effects meta-analysis. So, I am looking for the right packages and documentation. I know about meta and rmeta packages of R. Are there any more? What are the diffrences in brief? Can you please suggest some references that could be used as a guide for meta-analysis in R (or S-plus)?

Dear all, I could not draw a forest plot for meta-analysis under ramdon models using the rmeta package. The rmeta has a default function for MH (fixed-effect) model. Has the rmeta package been updated for such a function? Or someone revised it and kept a private code? I would appreciate it if you could provide some information on this question. Thanks, Andrew This email is intended

Hello, I'm ashamed to admit that I'm an R and meta-analysis neophyte just when my colleagues and I are attempting to run R for that latter purpose. We would like to construct a graph of the 95% confidence intervals of odds ratios (inverse odds ratios, actually). We are using the metaplot() function in the "rmeta" package. While we can construct a basic plot, we cannot configure

Dear R-list, I'd like to do a meta-analysis plot similar to install.packages('rmeta') require(rmeta) data(catheter) a <- meta.MH(n.trt, n.ctrl, col.trt, col.ctrl, data=catheter, names=Name, subset=c(13,6,5,3,7,12,4,11,1,8,10,2)) summary(a) plot(a) (see attached file) by using my own OR (Odds Ratio) and 95% Confidence Interval data set, which looks like

Hi All, Does someone have an idea of how to cleverly convert a categorical timeseries into a transition matrix? Ie, I have something like: x<- c(1,1,2,1,1,2,2,2,1,2), And I want a matrix with counts and/or probabilities: > tr <- matrix(c(2,3,2,2),2,2) > tr [,1] [,2] [1,] 2 2 [2,] 3 2 Meaning that there are two transitions from 1 to 1, two from 1 to 2, three from 2 to 1

Dear R users: In the example of meta-analysis (cochrane, package rmeta), I can not found the p-value of Test for overall effect, and some other indices (Z, I, weight and et al). How can I get the these indices listed? > library(rmeta) > data(cochrane) > cochrane name ev.trt n.trt ev.ctrl n.ctrl 1 Auckland 36 532 60 538 2 Block 1 69 5

Dear useRs, I'm trying to create a barplot like so: x=matrix(1:10,2,5) barplot(x,leg=c("left","right"),besid=T) The legend is placed in default position topright, however the data are plotted there too. I tried controlling the legend position by adding x="topleft" but this results in an error that x matches multiple formal arguments. Leaving out the legend

Is there a package in R that handles general linear (in-)equality + box constrained optimization? If it is not there, could anyone advise me which way to go? And/or point me to packages that solve these problems partially? best, ingmar -- Ingmar Visser Department of Psychology, University of Amsterdam Roetersstraat 15, 1018 WB Amsterdam The Netherlands http://users.fmg.uva.nl/ivisser/ tel:

Hello, I'm using the rmeta package to perform a meta analysis using summary statistics rather than raw data, and would like to analyze the effects in three different subgroups of my data. Furthermore, I'd like to plot this on one forest plot, with corresponding summary weighted averages of the effects displayed beneath each subgroup. I am able to generate the subgroup analyses by simply

Hi All, I'm building a package using C/C++ and Fortran code which usually runs fine. However I do get occasional bus errors around the time of exiting one of the C functions. Where do I need to be looking to solve this problem? Do bus errors stem from unmapped memory exceptions? How can I find out if that is what is happening while running R? Any hints greatly appreciated. Best, ingmar

Dear R-help, I'm trying to load the fGarch package and keep running into problems with tcltk: After succesfully instaling fGarch (and dependencies) I get: >library(fGarch) Loading required package: fBasics Loading required package: fImport Loading required package: fSeries Loading required package: robustbase Loading required package: fCalendar Loading required package: MASS Loading

Hello everyone, I want to do a meta-analysis of case-control studies on which an OR was computed based on a continuous exposure. I have found several several packages (metafor, rmeta, meta) but unless I misunderstood their main functions, it seems to me that they focus on two-group comparisons (binary independent variable), and do not have the option of using a continuous independent variable.

Dear R-help, I'm facing a problem with defining a repeated measures anova with weighted data. Here's the code to reproduce the problem: # generate some data seed=11 rtrep <- data.frame(rt=rnorm(100),ti=rep(1:5,20),subj=gl (20,5,100),we=runif(100)) # model with within factor for subjects/repeated measurements, no problem aov(rt~ti + Error(subj/ti),data=rtrep) #model with weights

Hi all, I am working on Macos x 10.3 (Panther) to build a package consisting of C/C++ code that is called from R. In the C/C++-sources I use several commands to print info to the console: std::cout << "info" << endl; and: Rprintf("info\n"); Both work fine when R is run on the command line but neither works when running Raqau (I did check the preference boxes

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

Hi all, I'm writing a vignette for my package, and I would like to include some of the package help files in there as well. Is there an easy way of doing so? I tried using R CMD Rdconv to generate latex files from .Rd files but I am not sure how to include these into a .Rnw file (ie the vignette source). The resulting file from Rdconv do not readily compile using latex ... The other option I

I use the lme function from the nlme library (or alternatively from the Matrix library) to estimate a random effects model. Both functions return the covariance matrix of the estimated parameters. I have the following question: Is it possible to retrieve the information matrix of such a model (ie from the fitted object)? In particular, the information matrix can be computed as a sum of individual

I had written a vignette and included a \usepackage{Rd} command to make it possible to include latex'ed Rd files in the vignette. However, when loading Rd.sty texShop produces the following error: l. 180 ...d}[1]{\ifmmode\bm{#1}\else\textbf{#1}\fi} This is on Max OS X 3.9 and R 2.0.1 Has anyone seen this before and/or is it problematic? I'm not sure whether the output suffers from this

Dear R-helpers, I need to compute probabilties of multinomial observations, eg by doing the following: y=sample(1:3,15,1) prob=matrix(runif(45),15) prob=prob/rowSums(prob) diag(prob[,y]) However, my question is whether this is the most efficient way to do this. In the call prob[,y] a whole matrix is computed which seems a bit of a waste. Is there maybe a vectorized version of dmultinom which

Dear R-helpers, When installing a source package I can suppress the compilation of .chm files by using the --docs="normal" option. Is it also possible to suppress the creation and checking of .chm files when calling R CMD check ? best, ingmar