similar to: Ordering box plots

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 just a point of curiosity with me. I want a sequence of numbers from 64 to 70, omitting the 2nd and 4th numbers. I can do it these ways: > seq(64, 70)[-c(2, 4)] [1] 64 66 68 69 70 > foo <- 64:70 > foo[-c(2, 4)] [1] 64 66 68 69 70 But how come this doesn't work? > 64:70[-c(2, 4)] [1] 64 65 66 67 68 69 70 Just wondering. -- Stuart Luppescu -=- slu .at.

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

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, 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)

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:

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

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

Is length(unique()) what you are looking for? Andy > From: Christoph Lehmann > > Hi I have a question concerning aggregation > > (simple demo code S. below) > > I have the data.frame > > id meas date > 1 a 0.637513747 1 > 2 a 0.187710063 2 > 3 a 0.247098459 2 > 4 a 0.306447690 3 > 5 b 0.407573577 2 > 6 b

I have a combined date and time. I would like to separate them out into two columns so I can do things such as take the mean by time across all dates. meas<-runif(435) nTime<-seq(1303975800, 1304757000, 1800) nDateT<-as.POSIXct(nTime, origin="1970-01-01") mat1<-cbind(nDateT,meas) means1<- aggregate(mat1$meas, list(nDateT), mean) This doesn't do anything as each day

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

Greetings, fellow R'ers. How can I get this frame in R: ID meas ID.1 meas.1 1 1.1 3 1.2 2 2.1 4 2.2 to look like this (stacking): ID meas 1 1.1 2 2.1 3 1.2 4 2.2 It's not really the reshape function (or is it?) because we can consider the additional columns, viz., ID.1 and meas.1, as independent of ID and meas so it is basically a stacking

Hello everybody. In my case, calculating multiple comparisons (Tukey) after lmer produced the following two errors: > sv.mc <- glht(model.sv,linfct=mcp(comp="Tukey")) Error in x$terms : $ operator not defined for this S4 class Error in factor_contrasts(model) : no 'model.matrix' method for 'model' found! What I have done before: > sv.growth <-

Y'all, I need to get the look of a "standard" fixed effect ANOVA table: anova(aov(meas~op*part,data=fs)) Analysis of Variance Table Response: meas Df Sum Sq Mean Sq F value Pr(>F) op 2 2.62 1.308 1.3193 0.2750 part 19 1185.43 62.391 62.9151 <2e-16 *** op:part 38 27.05 0.712 0.7178 0.8614 Residuals 60 59.50 0.992 when I perform a

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

maybe it's in the data? So here it comes. > sv.growth Grouped Data: length ~ meas | box_id meas spec comp water box_id sprouts leaves length long.sprout 1 1 Sv control moist 1 8.800000 37.80 211.2000 60.6 2 1 Sv xfull moist 2 7.000000 8.00 174.8000 62.8 3 1 Sv control moist 3 9.000000

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

I am very confused about this. I want to convert a string to a name so I can use it to extract an element of a data frame using `$'. Here is my (non-working) code: do.graph <- function (meas) { fn <- paste("a", meas, ".dat", sep='') themeas <- read.table(fn, header=F) ameas <- as.name(paste("a", meas, sep=''))