similar to: Multiple Conditional Tranformations

Hi All, I'm perplexed by the way the unclass function displays a factor whose labels have been swapped with the relevel function. I realize it won't affect any results and that the relevel did nothing useful in this particular case. I'm just doing it to learn ways to manipulate factors. The display of unclass leaves me feeling that the relevel had failed. I've checked three books

Hi All, I'm working on a class example that demonstrates one way to deal with factors and their labels. I create a function called myLabeler and apply it with lapply. It works on the whole data frame when I subscript it as in lapply( myQFvars[ ,myQFnames ], myLabeler ) but does not work if I leave the [] subscripts off. I would appreciate it if anyone could tell me why. The program below

Dear R-helpers, I know of two ways to reading data within an R program, using textConnection and stdin (demo program below). I've Googled about and looked in several books for comparisons of the two approaches but haven't found anything. Are there any particular advantages or disadvantages to these two approaches? If you were teaching R beginners, which would you present? Thanks, Bob

Hi All, I'm using the Hmisc summarize function and used list instead of llist to provide the by variables. It generated an error message. Is this a bug, or do I misunderstand how Hmisc works with lists? The program below demonstrates the error message. Thanks, Bob x<-1:8 group <- c(1,1,1,1,2,2,2,2) gender<- c(1,2,1,2,1,2,1,2) mydata<-data.frame(x,group,gender)

hi all - i'm having trouble using lme to specify a mixed effects model. i'm pretty sure this is quite easy for the experienced anova-er, which i unfortunately am not. i have a data frame with the following columns: col 1 : "Score1" (this is a continuous numeric measure between 0 and 1) col 2 : "Score2" (another continuous numeric measure, this time bounded between 0

Hi, all. I'd like to add legend on my graph but I can't. My code is follows. library(ggplot2) score1<-rnorm(100,0,5) score2<-rnorm(400,10,15) mydata<-data.frame(score1,score2) ggplot(mydata,aes(y=score2,x=score1))+geom_point()+stat_quantile(quantiles=c(0.50),col="red")+stat_quantile(quantiles=c(0.90),col="blue",size=2) I like to add legend indicating the

Dear colleagues, I have a problem which has bitten me occasionally. I often need to prepare graphs for many variables in a data set, but seldom for all. or for any large number of sequential or sequentially named variables. Often I need several graphs for different subsets of the dataset for a given variable. I run into similar problems with other needs besides graphing. What I would like to

Dear R-Helpers, Why does R show character missing values in vectors as NA and when stored in a data frame as <NA>? I've searched but did not find an explanation. Thanks, Bob > gender <- c("f","f","f",NA,"m","m","m","m") > gender [1] "f" "f" "f" NA "m" "m"

Hi All, I searched around to find the number of R packages currently available, but didn't find anything, so I choose all repositories & told it to install. The list contained about 2,856 (correcting roughly for those installed). But the list includes repetitions such as 19 names that begin with "bvbovine". Selecting only CRAN and CRAN(extras) I get 1,344. Is there an easier

Dear R-Users, I have a big data set "mydata" with repeated observation and some missing values. It looks like the format below: userid sex item score1 score2 1 0 1 1 1 1 0 2 0 1 1 0 3 NA 1 1 0 4 1 0 2 1 1 0 1 2 1 2 NA 1 2 1 3 1

Suppose I have a data frame like "dat" below. For some context, this is the format that represents student's taking a computer adaptive test. first.item is the first item that student was administered and then score.1 is the student's response to that item and so forth. item.pool <- paste("item", 1:10, sep = "") set.seed(54321) dat <- data.frame(id =

I've been playing around with various table tools, trying to construct a fairly simple cross-tab. It shouldn't be hard, but for some reason it turning out to be (for me). If I want to see how many men and how many women agree with a agree/disagree question (coded 1,0), I can do this: >attach(mydata) >mytable <- table(male, q1.bin) # gender and a binary response variable

Dear R-Helpers, I suspect I'm about to ask a FAQ, but I haven't been able to find an answer in the FAQ, AItR or an R Site Search. When I look at the methods of summary (below) it says, "Non-visible functions are asterisked". I looked at the help file for summary.princomp, which did not comment on it being non-visible. I ran its help file example, which printed visible output. I

Hi Folks, SAS Institute is adding official support for R: http://support.sas.com/rnd/app/studio/Rinterface2.html Cheers, Bob ========================================================= Bob Muenchen (pronounced Min'-chen), Manager, Research Computing Support U of TN Office of Information Technology Stokely Management Center, Suite 200 916 Volunteer Blvd., Knoxville, TN

I am new to R and have tried for a good while to figure out how to code this in R. The dataset below: FTIStandKey State County FTITract CoverType Ver_CT V_Origin V_SpGrp NAH6005-001 Texas Jasper NAH6005 PPLB-2000-U PPLB-2000-U P P NAH6005-002 Texas Jasper NAH6005 NHHX-1950-O NHHX-1950-I N H NAH6253-001 Texas Tyler NAH6253 PPLB-2001-U PPLB-2001-U P P

Hi All, We have all had to face skeptical colleagues asking if software made by volunteers could match the quality and accuracy of commercially written software. Thanks to the prompting of a recent R-help thread, I read, "R: Regulatory Compliance and Validation Issues, A Guidance Document for the Use of R in Regulated Clinical Trial Environments (http://www.r-project.org/doc/R-FDA.pdf).

Dear HelpeRs, I'm confused about the role of quotes around package names on the library and detach functions. Books on R use both approaches: library(Hmisc) describe(mydata) detach(package:Hmisc) and library("Hmisc") describe(mydata) detach("package:Hmisc") The help file for detach says "quoted or unquoted" and the help file for library says about the

Hi All, I'm trying to understand the difference between do.call and lapply for applying a function to a list. Below is one of the variations of programs (by Marc Schwartz) discussed here recently to select the first and last n observations per group. I've looked in several books, the R FAQ and searched the archives, but I can't find enough to figure out why lapply doesn't do what

Hi All, I'm learning JGR 1.4-15 with R 2.4.1 in Windows XP (all patches applied). JGR looks great but I'm having trouble getting the data editor to save my results. I don't see anything in R-help about it. Here are the steps I followed: 1. I chose "Tools>Object Browser" & double-clicked on a data frame, "mydata". 2. A spreadsheet editor popped up and

Hi All, If I need to stack two data frames, I can use rbind, but it requires that all variables exist in both sets. I can make that happen, but other stat packages would figure out where the differences were, add the missing variables to each, set their values to missing and stack them. Is there a more automatic way to do that in R? Below is an example program. Thanks, Bob # Top data frame has