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Hi, How can I configure R to allow http connection (through company firewall)? Your help are greatly appreciated! Wei Ding, Ph.D. Schering-Plough Research Institute 2015 Galloping Hill Road Kenilworth, NJ 07033 Tel: (908) 740-2592 Fax: (908) 740-7664 ********************************************************************* This message and any attachments are solely for the intended rec...

Hi All.., I need to do the following repetitive jobs: seg71 <- read.csv("C:/Awork/geneAssociation/removed8samples/neuhausen71/seg.pr3.csv", head=T) seg71$id <-"sn71" seg72 <- read.csv("C:/Awork/geneAssociation/removed8samples/neuhausen72/seg.pr3.csv", head=T) seg72$id <-"sn72" seg73 <-

David: I believe your response on SO is incorrect. This is a standard OFAT (one factor at a time) design, so that assuming additivity (no interactions), the effects of drugA and drugB can be determined via the model you rejected: For example, if baseline control (no drugs) has a response of 0, drugA has an effect of 1, drugB has an effect of 2, and the effects are additive, with no noise we

Hi Bert and David, Thank you so much for willingness to spend some time on my problem!!! I have some statistical knowledge (going to get a master in applied statisitics), but do not have a chance to purse a phD for statistics, so I am always be careful before starting to do analysis and hope to gather supportive information from real statisticians. Sorry that I did not tell more info about

Hi Bert, I am very sorry to bother you again. For the following question, as you suggested, I posted it in both Biostars website and stackexchange website, so far no reply. I really hope that you can do me a great favor to share your points about how to explain the coefficients for drug A and drug B if run anova model (response variable = drug A + drug B). is it different from running three

Hi Sarah, Thank you so much!! I got your good ideas. Ding -----Original Message----- From: Sarah Goslee [mailto:sarah.goslee at gmail.com] Sent: Friday, May 11, 2018 11:40 AM To: Ding, Yuan Chun Cc: r-help mailing list Subject: Re: [R] add one variable to a data frame [Attention: This email came from an external source. Do not open attachments or click on links from unknown senders or

Dear R users, I need to analyze data generated from a partial two-by-two factorial design: two levels for drug A (yes, no), two levels for drug B (yes, no); however, data points are available only for three groups, no drugA/no drugB, yes drugA/no drugB, yes drugA/yes drug B, omitting the fourth group of no drugA/yes drugB. I think we can not investigate interaction between drug A and drug B,

This list provides help on R programming (see the posting guide linked below for details on what is/is not considered on topic), and generally avoids discussion of purely statistical issues, which is what your query appears to be. The simple answer is yes, you can fit the model as described, but you clearly need the off topic discussion as to what it does or does not mean. For that, you might try

Thank you, your suggestion is simpler and logically better. I had impression that the last object in a function gets returned, so I did not add the print function at the bottom line of the function definition. Returning an object and graph the object are different process, I am a beginner for writing R function and need to find a good guide source about writing R functions. If you know a good

CentOS Errata and Bugfix Advisory 2017:0302 Upstream details at : https://rhn.redhat.com/errata/RHBA-2017-0302.html The following updated files have been uploaded and are currently syncing to the mirrors: ( sha256sum Filename ) i386: 6b6b750c5843f85219890391c805bf2dee76e254549abf23978aad260571f7e9 libbasicobjects-0.1.1-11.el6_8.1.i686.rpm

CentOS Errata and Enhancement Advisory 2011:0974 Upstream details at : https://rhn.redhat.com/errata/RHEA-2011-0974.html The following updated files have been uploaded and are currently syncing to the mirrors: ( md5sum Filename ) i386: 808e0b8df8d5397c6721e71b7ffaa0d3 libcollection-0.6.0-10.el5.i386.rpm a330b1f325f45268b2347e34c2c415e5 libcollection-devel-0.6.0-10.el5.i386.rpm

CentOS Errata and Enhancement Advisory 2011:0974 Upstream details at : https://rhn.redhat.com/errata/RHEA-2011-0974.html The following updated files have been uploaded and are currently syncing to the mirrors: ( md5sum Filename ) x86_64: b30c6f98c842d509c126e328dcfb162a libcollection-0.6.0-10.el5.i386.rpm 2885e2691aa154b8e694331db1455fd1 libcollection-0.6.0-10.el5.x86_64.rpm

> On Mar 5, 2018, at 8:52 AM, Ding, Yuan Chun <ycding at coh.org> wrote: > > Hi Bert, > > I am very sorry to bother you again. > > For the following question, as you suggested, I posted it in both Biostars website and stackexchange website, so far no reply. > > I really hope that you can do me a great favor to share your points about how to explain the

Hi Richard, Thank you so much!! I understand the problem now, I assign a name to the "ggsurvplot" object and then add print(fig) at bottom of function definition, now figure gets printed on screen. Ding # function to generate RFS curves RFS <- function( inputfile, N ) { cluster<- survfit(Surv(RFS_days2, OV_Had_a_Recurrence_CODE) ~ clusters, data =

But of course the whole point of additivity is to decompose the combined effect as the sum of individual effects. "Mislead" is a subjective judgment, so no comment. The explanation I provided is standard. I used it for decades when I taught in industry. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into

Sarah's solutions are good, and here's another, even more basic: tmp1 <- unique(dat1$B) tmp2 <- seq_along(tmp1) dat1$C <- tmp2[ match( dat1$B, tmp1) ] > dat1 N B C 1 1 29_log 1 2 2 29_log 1 3 3 29_log 1 4 4 27_cat 2 5 5 27_cat 2 6 6 1_log 3 7 7 1_log 3 8 8 1_log 3 9 9 1_log 3 10 10 1_log 3 11 11 3_cat 4 12 12 3_cat 4 As a single line

That is certainly OK, but you can also just use print(ggsurvplot(...)) as your final statement. out <- RFS( ...) would then return the ggsurvplot object *and* graph it. Any good R tutorial or a web search will provide more details on function returns, which you might find useful. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and

> On Mar 5, 2018, at 3:04 PM, Bert Gunter <bgunter.4567 at gmail.com> wrote: > > But of course the whole point of additivity is to decompose the combined effect as the sum of individual effects. Agreed. Furthermore your encoding of the treatment assignments has the advantage that the default treatment contrast for A+B will have a statistical estimate associated with it. That was a

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Hi All, I have a data frame dat1: dat1 <-data.frame(N=seq(1, 12,1), B=c("29_log","29_log", "29_log", "27_cat", "27_cat", "1_log", "1_log", "1_log", "1_log", "1_log",