similar to: CI wiskers

Dear Bert, thank you for suggestion. I am aware of R-help function. I must apologize, my earlier question could lead to assumptions otherwise. As you can see below, I only get Std. error but not lower and Upper CIs. I was wondering if there is another argument or method, could give CIs which I cannot find anywhere. Thanks Adrian > Nsurv <-

??? Both ?survit.object (linked in the see also section of ?survfit) and ?summary.survfit give you this information. Do you not know how to use R's help faciities -- in which case you should learn them now; see ?help -- or have I misunderstood your query? Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it."

Hi I am not sure hiw to get thr CI from summary function on the survfit object. I can get the percent survival for 2 years from survfit object but I dont get Confidence intervals Could anyone suggest a hint Thanks Adrian [[alternative HTML version deleted]]

Did you not notice the conf.type = "none" argument to your survfit call and the associated documentation in the survfit help? -- Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Sat, Aug 26, 2017 at 5:18 PM, Adrian Johnson

This is a suggestion for adding to rsync an option "--checksum-path=PROGRAM". Once this option is given, provided it is accompained by option "--checksum", both the receiving and sending side of rsync would compute checksums calling PROGRAM, instead of the usual checksum program. Why is this usefull? Suppose I have two collections of MP3 files at different locations which I

Dear R users, I am trying to use xyplot to draw group mean and CI. The following is the sample code. But I want: 1. Use different colors and symbols to draw individual points, CI and the lines connect group means from different time points; 2. Add jitters to x axis to allow CIs not be overlapped Could anyone modify the attached code to achieve this? Thanks library(lattice)

Please forgive the incorrect threading on this reply to Tom Stellard's RFC. > I would like to start using GitHub Actions[1] for CI testing on the release/* > branches. As far as I know we don't have any buildbots listening to the > release branches, and I think GitHub Actions are a good way for us to > quickly bring-up some CI jobs there. Personally, I feel that Tom's

> I think my concern is that LLVM could prove to be too big and require too many resources for github's infrastructure. How many patches go into LLVM a day, and how many build and test jobs does GitHub allow users to run concurrently before being throttled? Please, no one confuse "what should be LLVM's official CIs" with "what can we do to make it easier for individuals

I am having trouble understanding (i.e. getting) confidence intervals from the survey package. I am using R version 2.8.1 (2008-12-22) and survey package (3.11-2) on FC7 linux. To simplify my question I use an example from that package: R> data(api) R> dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc) R> (tst <- svyby(~api99, ~stype,

Hi, I'm having trouble using dates (created using library(chron)) as groupings for a boxplot. I have 10 repeat measurements of a variable within an individual day. The measurements were done over 10 days. I would like to plot the measurements as a box and wisker plot (using boxplot or something similar) where the days (as chron object) would be the grouping and the repeated measurements

Dear friends, I'm probably wrong but is there anything better than bootstrap to get a confidence interval of the median from a population with unspecified distribution ? Best wishes Troels Ring, Aalborg, Denmark

On 02/06/2020 08:41 AM, Russell Gallop wrote: > Hi Tom, > > Thank you for setting this up. It's very useful. > > One question about what this builds. It only builds "ninja check-all", not "ninja all"[1]. check-all isn't a strict superset of all so while this covers most things, this does miss building a few things such as: > bin/clang-offload-wrapper

For boxplot(), is it possible to pass in a parameter to change the default way that the 1st and 3rd quartiles are computed? (specifically, I'd like to use type 6 described in the quantile function). Also, what are the options for how outliers are computed, and how can one change them? Thank you [[alternative HTML version deleted]]

Overview ======== This module implements the Center for Internet Security (CIS) Security Configuration Benchmark for Red Hat Enterprise Linux 6 v.1.1.0 (avilable at http://benchmarks.cisecurity.org). Each scored control has been implemented as a class or a custom fact. Installation ============ Please either: - Clone git repo from https://github.com/arildjensen/cis-puppet - Run "puppet

I have a system running rsync in daemon mode, the version information: > rsync --version rsync version 2.6.8 protocol version 29 On another system I have: > authoritative# rsync --version rsync version 3.0.7 protocol version 30 I have the following problem when trying to fetch files from the system running the old daemon: # /usr/local/bin/rsync --protocol=29 -vvvvvvvv

Hello group, I am learning R and I am new to many concepts.I face the following errors when I am trying to execute the following. I have 4 text files with protein accession numbers. I wanted to represent them in a venn diagram and for that I using intersect and setdiff functions. My data looks like this: file1.txt (c): NP_000005 NP_000020 NP_000030 NP_000053 file2.txt(e): NP_000005 NP_000020

Dear R-Experts, Here below is my R code (reproducible example) to calculate the confidence intervals around the spearman coefficient. ########## C=c(2,4,5,6,3,4,5,7,8,7,6,5,6,7,7,8,5,4,3,2) D=c(3,5,4,6,7,2,3,1,2,4,5,4,6,4,5,4,3,2,8,9) cor(C,D,method= "spearman") library(boot) myCor=function(data,index){ cor(data[index, ])[1,2] } results=boot(data=cbind(C,D),statistic=myCor, R=2000)

Hi, I want to plot grouped bars to compare 95% confidence interval estimates from two models. Each bar represents a 95% confidence interval estimate of a coefficient from one of the two models. Each group represents confidence interval estimates of the same coefficient from the two models. I think such a bar plot will nicely present whether 95% confidence interval estimates of the same

Hi, I am trying to construct a logistic regression model from my data (104 patients and 25 events). I build a full model consisting of five predictors with the use of penalization by rms package (lrm, pentrace etc) because of events per variable issue. Then, I tried to approximate the full model by step-down technique predicting L from all of the componet variables using ordinary least squares

Hi, I am attempting to set the confidence limits on a ls means plot as follows: mult<-glht(lm(effectModel, data=statdata, na.action = na.omit), linfct=mcp(mainEffect="Means")) meanPlot <- sub(".html", "meanplot.jpg", htmlFile) jpeg(meanPlot) plot(mult, main=NA, xlab=unlist(strsplit(Args[4],"~"))[1]) This produces 95% CIs by default but I would