similar to: eRm package - Rasch simulation

I'm trying to kick off some of the rust and learn some of the R packages for Rasch modeling. When I tried using the eRm package, I get item difficulty estimates for all my items accept the first (in terms of order) item. #Begin code library(eRm) r.simulation <- sim.rasch(20,100) r.data <- r.simulation$items #eRm results erm.rasch <- RM(r.data) names(erm.rasch) erm.items <-

Dear R Users, I am using the LLTM and the LRSM functions in the eRm package to do repeated measurements where there are 2 measurement points for a list of 10 items. I am trying to get ability estimates but am having trouble. I don't think that it is appropriate to use the pmat function since the person parameters are based on all 20 items. Rather, I think it would be more appropriate to

Hi, I am trying to do an LRSM Rasch analysis for 72-item data. 67 of the items are binary, and 5 are ternary. I have tried it with and without a specified matrix, and cannot get it to work. The primary problems I am having are: 1. Without a matrix, I get an error: Error in `rownames<-`(`*tmp*`, value = betanames) : length of 'dimnames' [1] not equal to array extent This is from

Dear useRs, new and updated features in eRm 0.9-6 for extended Rasch modeling: - infit and outfit mean-square statistics added to functions personfit() and itemfit(). - new method: plotPImap() plots a person-item map (cf. Bond & Fox, 2007), i.e., a map of locations of item (and threshold) parameters, and the distribution of person parameters. - new options in plotGOF(): 'conf':

Dear useRs, new and updated features in eRm 0.9-6 for extended Rasch modeling: - infit and outfit mean-square statistics added to functions personfit() and itemfit(). - new method: plotPImap() plots a person-item map (cf. Bond & Fox, 2007), i.e., a map of locations of item (and threshold) parameters, and the distribution of person parameters. - new options in plotGOF(): 'conf':

Dear all, I'm working on ability estimates using Rasch model. Using the "ltm" package, the procedure is quite simple: ## Factor Scores for the Rasch model fit <- rasch(LSAT) factor.scores(fit) What about Partial Credit Model (PCM)? For PCM I use PCM function from eRm package. Is there any similar function like factor.scores to estimate ability scores using PCM model? Best,

Hi, I am running the non-parametric rasch model tests using eRm. I have a reasonably large dataset for this type of exercise (110 items, 248 persons). I run: > allb2=as.matrix(allb) > rsample <- rsampler(allb2, ctr) > t102<-NPtest(rsample, method="T10") #global test, subgroup inv and receive error message as follows. "Error in m[idx1, idx2] <- 1 : subscript out

I am trying to create a frequency distribution and I am a bit confused. Here are the commands I have entered: > data <- read.csv(file="40609_sortedfinal.csv",head=TRUE,sep=",") > NumberOfActionsByStatus = data$STATUS > NumberOfActionsByUser = data$ETS_LOGIN > NumberOfBidOffer = data$BID_OFFER > NumberOfActionsByUser.freq = table(NumberOfActionsByUser) >

I'm new to 'R', so forgive me if I've used the wrong term. I'd like to model some Likert-style items using Rasch methods. I've been unable to find mention of these for 'R'. Would someone happen to know of any? Thanks in any case. Bill ------------ "It is the time that you have wasted for your rose that makes your rose so important."--St-Exupery

I'm testing an education assessment (evaluating quantitative skills in biology students) for reliability. I used cronbach's alpha, but got a really low alpha which I think is likely due to my small number of questions (12) and the fact that the questions are of varying difficulty. After a lot of reading, it looks like Rasch models are probably a more appropriate tool for my question so

This is a very basic question, but I am a bit confused with optim. I want to get the MLEs using optim which could replace the newton-raphson code I have below which also gives the MLEs. The function takes as input a vector x denoting whether a respondent answered an item correctly (x=1) or not (x=0). It also takes as input a vector b_vector, and these are parameters of test items (Rasch estimates

I am writing a small function to approximate an integral that cannot be evaluated in closed form. I am partially successful at this point and am experiencing one small, albeit important problem. Here is part of my function below. This is a psychometric problem for dichotomously scored test items where x is a vector of 1s or 0s denoting whether the respondent answered the item correctly (1) or

Dear R users, I still feel new to R so please apologize if I am doing something stupid here. My use of the polygon() function produces a result that I cannot comprehend: In a plot, I would like to shade the area below a normal distribution. However, I do not want the entire area to be shaded, but just the area on the right side of a vertical line that I draw through the distribution (in

Dear List I apologize for the multiple postings. After being in the weeds on this problem for a while I think my original post may have been a little cryptic. I think I can be clearer. Essentially, I need the following a <- c(2,3) b <- c(4,5,6) (2*4) + (2*5) + (2*6) + (3*4) + (3*5) +(3*6) But I do not know of a built in function that would do this. Any suggestions? -----Original

How does one use the vcut from Vorbis-tools package? I tried to enter samples, miliseconds, seconds, h:mm:ss as cut point, but nothing worked (I even tried to enter 1 as cutpoint, but I always got "Cutpoint not within stream." message)... I'm doing this on Windows, if it matters... -- Jernej Simoncic, jernej.simoncic@guest.arnes.si http://www2.arnes.si/~sopjsimo/ ICQ: 26266467

Dear all, I'm trying to manage with user defined split function in rpart (file rpart\tests\usersplits.R in http://cran.r-project.org/src/contrib/rpart_3.1-34.tar.gz - see bottom of the email). Suppose to have the following data.frame (note that x's values are already sorted) > D y x 1 7 0.428 2 3 0.876 3 1 1.467 4 6 1.492 5 3 1.703 6 4 2.406 7 8 2.628 8 6 2.879 9 5 3.025 10 3 3.494

I have a function that I am currently using very inefficiently. The following are needed to illustrate the problem: set.seed(12345) dat <- matrix(sample(c(0,1), 110, replace = TRUE), nrow = 11, ncol=10) mis <- sample(1:110, 5) dat[mis] <- NA theta <- rnorm(11) b_vector <- runif(10, -4,4) empty <- which(is.na(t(dat))) So, I have a matrix (dat) with some values within the matrix

Dear List: We are generating data such that students are clustered in schools for some item response data for a simulation study. One component of our simulation is to generate measurement error from a logistic distribution with a mean of 0 and standard deviation of 1.7 to match the logistic curve of the Rasch model. We are generating an error term for each of the 40 hypothetical test items a

Dear Mrs Rachel Pearce, I am looking for a function "cutpt-coxph" in R - like you did some years ago. How have you solved the problem? Have you found it or a similar function? thank you, Sincerely, Friederike "The title says it all really; I am looking for a function along the lines of cutpt.coxph as described in "Survival Analysis Using S" (Tableman and Kim), Chapter

I am trying to run WinBUGS 1.4 from the Ubuntu 6.10 Linux distribution. I am using the R2WinBUGS packages with the source file listed below. WinBUGS appears to run properly, but I get the following message after WinBUGS starts in WINE. Does anyone know what may be causing this error and what the correction may be? Thanks ERROR MESSAGE: fixme:ole:GetHGlobalFromILockBytes cbSize is 13824