Hi Jim: Thank you very much for your help in this topic.
with many thanks abou ______________________ *AbouEl-Makarim Aboueissa, PhD* *Professor, Statistics and Data Science* *Graduate Coordinator* *Department of Mathematics and Statistics* *University of Southern Maine* On Sat, Nov 13, 2021 at 8:47 PM Jim Lemon <drjimle...@gmail.com> wrote: > Hi Abou, > Perhaps this will be helpful. Be aware that you will cop some flak for > putting error bars on a bar plot. > > aadat<-data.frame(group=c(rep("Exp",50),rep("Con",50)), > v1=sample(0:1,100,TRUE), > v2=sample(0:1,100,TRUE), > v3=sample(0:1,100,TRUE), > v4=sample(0:1,100,TRUE), > v5=sample(0:1,100,TRUE)) > ggps<-function(x,group) { > gns<-as.vector(table(group)) > return(by(x,group,sum)/gns) > } > testggps<-data.frame( > group=c("A","A","A","B","B","B","B","C","C","C","C","C"), > x=c(1,0,1,1,0,1,0,1,1,0,0,0)) > aaprop<-sapply(aadat[,2:6],ggps,aadat[,1]) > library(plotrix) > barpos<-barp(aaprop,ylim=c(0,0.65),col=c(2,3),names.arg=colnames(aaprop)) > legend(2.5,0.65,c("Con","Exp"),fill=c(2,3)) > dispersion(barpos$x,barpos$y,ulim=aaprop/10) > > Jim > > On Sun, Nov 14, 2021 at 11:01 AM AbouEl-Makarim Aboueissa > <abouelmakarim1...@gmail.com> wrote: > > > > Dear All: > > > > > > > > I do have a binary data set with multiple variables, event = 1 in all > > variables. As an example, I attached a data set with 6 variables. The > first > > column is the grouping variable. Then the next 5 columns are the binary > > data for 5 variables. > > > > > > > > - Can we compute the confidence interval for the difference between the > two > > proportions of the event = 1 in both groups (say: G1 – G2) for the 5 > > variables in one shut. > > > > > > > > - I also need to create the Bar plot of individual proportions (both > groups > > side-by-side) and add the confidence intervals bar for the 5 variables in > > one graph. > > > > > > > > > > > > Example.Data <- read.table(file="F/Example_Data_for_R.csv", header=T, > > sep=",") > > > > Example.Data > > > > attach(Example.Data) > > > > > > > > > > > > > > > > #### For example, this is how I use the prop.test() function to get the > CI > > for p1-p2 > > > > > > > > x12 <- c(x1, x2) > > > > n12 <- c(n1, n2) > > > > prop.test(x12, n12, conf.level = 0.95)$conf.int > > > > > > > > But, I am not sure how to use it for raw data, and for multiple pairs of > > data in one shut if possible. > > > > > > > > With many thanks in advance > > > > Abou > > ______________________ > > > > > > *AbouEl-Makarim Aboueissa, PhD* > > > > *Professor, Statistics and Data Science* > > *Graduate Coordinator* > > > > *Department of Mathematics and Statistics* > > *University of Southern Maine* > > ______________________________________________ > > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.