similar to: Forest Plot

Hi, I am traying to implement an STAR model, but I have some problems. I am following the instruction of the model, that they are in: http://bm2.genes.nig.ac.jp/RGM2/R_current/library/tsDyn/man/star.html that they are from: http://bm2.genes.nig.ac.jp/RGM2/pkg.php?p=tsDyn The model is: star(x, m=2, noRegimes, d = 1, steps = d, series, rob = FALSE, mTh, thDelay, thVar, sig=0.05, trace=TRUE,

Odette > Wondering how can I generate "Akaike weight" with R? I know the description, > but is there any function to generate by R on the web-site or R library? > I am using GLM or GLMM (family=binomial), so would be appreciated if you > help me. You could have a look at this. http://bm2.genes.nig.ac.jp/RGM2/R_current/library/aod/man/summary.aic.html Which is in the OAD

Hi Kim and Others, Can anyone please help me on how can I edit default labels ( "Study 1", "Study 2",...) using forest() - same question as below. Which option I should try? It would be a great help. Thanks in advance, On Sun, Dec 13, 2009 at 7:14 PM, Kim Jung Hwa <kimhwamaillist@gmail.com>wrote: > Hi All, > > I'm using forest() from metafor package to

Dear R Helpers Which package is available for estimatine the parameters of three parameter FRECHET distribution. Also, how to generate the random numbers for Frechet using these three estimated parameters. Thanking in advance Maithili

Dear List, R ist somtimes a bit frustrating... I ran the example from http://bm2.genes.nig.ac.jp/RGM2/R_current/library/QRMlib/man/plotMultiTS.html and I get an error. Has someone an explanation for this? Thanks a lot, Steve CODE: library(R.utils) library(tseries) library(wmtsa) library(waveslim) library(brainwaver) library(timeSeries) library(QRMlib) > ?plotMultiTS >

Dear R-Helpers, I have a short question related to heatmap.2 function. I wanted to change the dimension of each cell in the heatmap drawn by this function. here is a reproducible example from the help page library(gplots) data(mtcars) x <- as.matrix(mtcars) rc <- rainbow(nrow(x), start=0, end=.3) cc <- rainbow(ncol(x), start=0, end=.3) hv <- heatmap.2(x, col=cm.colors(255),

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

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

Hi, I hope somebody can help me with this issue: I am doing population pyramids using the barplot command, so in the left side I have male age structure and in the right side the female age structure. To plot the male age structure I put the data in negative numbers. Now, I want to change the sign in the bar plot in such way that I have no-sign numbers, both in left and right side of the graph. I

Hi, I have the two vectors mean and sd of individual columns, but I am unsure how to generate bar charts with the standard deviation, even after looking the help of barplot and barplot.2. [[alternative HTML version deleted]]

Dear R Users, Do you know of an existing function that allows the production of sensitivity and specificity forest plots? See the following for an example:

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:

Hello I'm running into a variety of limitations with my computer complaining that it doesn't have sufficient memory. It is a Dell Latitude D630 Duo Core CPU T7700 @ 2.40 GHz, with 3.50 GB RAM. I'm working with relatively large dataframes > dim(AllYears) returns 4071840 records with 13variables sometimes this complains that it can not allocate vectors of 16.0 Mb and will

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,

Hello, Is it possible to have two meta-plots in one graph (not par(mfrow=c(2,1))? But somthing like  library(metafor)  library("igraph")    if (interactive()) {     forest(dat.Treat$RR, ci.lb=dat.Treat$lower, ci.ub=dat.Treat$upper, xlab="Relative Risk",slab=dat.Treat$ID,refline=1)     forest(dat.Control$RR, ci.lb=dat.Control$lower, ci.ub=dat.Control$upper, xlab="Relative

I have a one-variable data set in R. The plot of histogram of my numerical variable suggests an inverse gaussian distribution. How can I obtain best estimation for the two parameters of inverse gaussian based on my data? Thanks. -- View this message in context: http://n4.nabble.com/estimate-inverse-gaussian-in-R-tp949692p949692.html Sent from the R help mailing list archive at Nabble.com.

Hello, I am learning to use the metafor package to conduct meta-regression analyses for a systematic review on multidisciplinary care interventions in chronic kidney disease. For the forest plots, I can't figure out how to plot unadjusted and adjusted models on the same plot. From top to bottom, I would like to be able have the unadjusted plot, the multivariate adjusted plot, then each

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

Hi. I have data which i would want to assess the degree of agreement between two assays, e.g., to evaluate reproducibility or for inter-rater reliability. I have used the Pearson product-moment correlation coefficient. It looks good ranginging between 0.90 to 0.998. Though this looks good. I am told the Concordance correlation coefficient will give a better picture of how reproducible the assay

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,