similar to: Omitting members of a sequence

Hello all, I want box plots by group to display in order of increasing mean (or median) of each group but can't seem to figure it out and couldn't find anything on R-seek, either. My data looks like this: meas unit sid grade rsprti 1 2.24 1002 99999902 NA 0.8600000 2 3.04 1007 43589520 3 0.9400000 3 4.95 2002 39910470 5 1.5300000 4 2.24 2002 39986280 5

Hello, This one is very perplexing. I have teacher observation data, with factors teacher ID, observer ID, component, grade and subject. When I do this, aov(data=ratings.prin.22, rating ~ obsid.f + tid.f + subject.f + grade.f + comp.f) I get this: Terms: obsid.f tid.f grade.f comp.f Residuals Sum of Squares 306.23399 221.38173 1.70000 14.52831 279.05780 Deg. of

Hello all, I need to extract rows and columns from a data frame and put them in a matrix. In some cases, there are no rows in the data frame meeting the selection criteria. For those rows I want to put a row of 0's in the matrix. Here's my clumsy code: tab1.m1 <- matrix(0, nrow=2, ncol=4) tab1.m1[1,] <- ifelse(length(as.matrix(tab1[tab1$comp==the.comp & tab1$schlid==the.schl

Hello, This is my first time trying to use plyr, and I'm getting nowhere. I have teacher ratings data (1:4), on 10 components, by external observers and internal observers, in schools in areas. I want to calculate the percentage of each rating given on each component, by each type of observer, within each school, within each area. The data look like this: unit area ext.obs rating comp 11

Hello, I am having trouble getting counts of values in rows of a data frame. I'm trying to use apply, but it's not working. This gives a sample of the kind of data I'm working with: rating.1 <- factor(sample(1:4, size=10, replace=T), levels=1:4) rating.2 <- factor(sample(1:4, size=10, replace=T), levels=1:4) rating.3 <- factor(sample(1:3, size=10, replace=T), levels=1:4)

Hello, I have to construct 5 new columns in a data frame depending on the value of another of the columns in the data frame. The only way I could figure out to do this was to subset the data frame five times, do the variable construction, and then rbind the subsets back together. Here's part of the code I used: read001 <- read[read$existstr=="001",] read001$era1end <- NA

Dear Whom it may concern, I need help to figure the "macro" function in R: I need to plot the different data sets by a plotxyf function, I want the title to be different for different data set. # get the data set final.xyf<- xyf(data=as.matrix(my.final), Y=classvec2classmat(final$outcome), xweight = 0.5, grid=somgrid(5, 4, "hexagonal")) #plot function

Hello, As you can see from my signature in this message, I use the R fortune function to generate a fortune, which is then fed to the signature program, which constructs a named pipe containing the fortune-bearing sig, which is then included in mail messages. The problem is that it's got extraneous junk in it and I can't figure out how to get rid of it. This is the command that generates

My mind has become corrupted by having to use SAS too much. I wanted to calculate the difference of elements of two vectors if the signs are the same. I tried it the corrupted way first: if (effects1[,3] < 0 & effects0[,3] < 0) { imprv1 <- effects0[,3] - effects1[,3] } else if (effects1[,3] > 0 & effects0[,3] > 0) { imprv1 <- effects1[,3] - effects0[,3] } else {

Hello, I want to add wireless capability to my Gentoo-linux based firewall/router at home, so I bought a Netgear MA311 PCI and installed the hostap package. I load the hostap_pci module and the wlan0 interface comes up fine. I can detect the signal from a wireless enabled laptop. Now I'm thinking I'm going to bridge the wlan0 interface and the eth1 interface, and run the firewall with br0

I'm trying to shade part of a density plot. The code I'm trying (using the Old Faithful data as an example) is something like this: # The Old Faithful geyser data data(faithful) d <- density(faithful$eruptions, bw = "sj") plot(d) polygon(d[d$x>4], col = "wheat") I expected that the part of the curve to the right of 4 on the x axis should be shaded, but nothing

Hello, I'm trying to do a little rlm of some data that looks like this: UNIT COHORT perdo adjodds 1010 96 0.39890 1.06894 1010 97 0.48113 1.57500 1010 98 0.36328 1.21498 1010 99 0.44391 1.38608 It works fine like this: rlm(perdo ~ COHORT, psi=psisquare) But the problem is that I have about 100 UNITs, and I want to do a

Under MacOS I had R64 executive and it was clear. Under Ubuntu, which I do not have administrative rights to, there is only R executive. It seems that I can allocate more than 3GB of memory, however not everything seems to work the same/right as with R64 under MacOS. Pms.

Dear All, does anybody know of a package (working under Linux) for multilevel IRT modelling? I'd love to do this without having to go on WINSTEPS or the like.. thanks for the attention! Federico Andreis ----- Dr. Federico Andreis Universit? degli Studi di Milano-Bicocca, PhD Student MEB Department, Karolinska Institutet, Stockholm, Visiting PhD Student -- View this message in context:

I'm trying to install packages in Gentoo Linux using install.packages(). The packages download fine, but when it comes to installation, I get this message: WARNING: ignoring environment value of R_HOME /var/tmp/portage/R-1.5.1/image//usr/lib/R/bin/Rcmd: /var/tmp/portage/R-1.5.1/image//usr/lib/R/bin/Rcmd: No such file or directory I have the R_HOME set to the correct value (/usr/lib/R), but I

hello R, This is about simulation in psychomtrics in IRT in R. I want to simulate b parameters(item difficulty) with moments of fixed values of mean, st.d, skewness and kurtosis. Is there any specific IRT package in R with those functions to control those moments? I have seen other programs that can control mean and st.d but not skewness and kurtosis. Thank you, helen L [[alternative HTML

Hi there, I want to make trajectory plots for data as follows: ID time y 1 1 1.4 1 2 2.0 1 3 2.5 2 1.5 2.3 2 4 4.5 2 5.5 1.6 2 6 2.0 ... That is, I will plot a growth curve for each subject ID, with y in the y axis, and time in the x axis. I would like to have all growth curves in the same plot. Is there

I can't remember the programming term -- ``implicit declaration''? Has this changed between 1.4.1 and 1.5? This code used to run as is: for (i in 1:length(diff.time)) { if (diff.time[i] < 16) { total.time[i] <- ifelse(i==1, 7.5, total.time[i-1]) + diff.time[i] last.time[i] <- 0 } else { total.time[i] <- 7.5 last.time[i-1] <- 1 } } Now in 1.5 I

Do MD5 digests exist somewhere for the source packages? If not, is there some other way to verify the integrity of the files we've downloaded? Thanks. -- Stuart Luppescu -=- s-luppescu at uchicago.edu University of Chicago -=- CCSR $B:MJ8$HCRF`H~$NIc(B -=- Kernel 2.4.19-xfs-r1 There *is* no such thing as a civil engineer. -------------- next part

Is there something unusual about the way BATCH jobs are run? I ran a job like this: nice R CMD BATCH program.R It ran for a little while and then it starting eating up huge amounts of resources. Here is the entry from top: top 17:34:10 up 36 days, 8:10, 4 users, load average: 13.11, 6.85, 3.7 0 Tasks: 173 total, 6 running, 167 sleeping, 0 stopped, 0 zombie Cpu(s): 0.1%us, 99.4%sy,