similar to: eRm - Rasch modeling - First item missing from estimation

When I try to create a Rasch simulation of data using the sim.rasch function, I get more items than I intend #My code library(eRm) #Number of items k <- 20 #Number of participants n <- 100 #Create Rasch Data #sim.rasch(persons, items, seed = NULL, cutpoint = "randomized") r.simulation <- sim.rasch(n,k) I end up with 20 participants and 100 items, but the instructions say

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 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

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':

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

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 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) >

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

Dear R-List, I tried to fit a partial credit model using the "pcmdat" from eRm-package comparing the results of mirt, eRm, ltm and winsteps. The results where quite different, though. I cannot figure out what went wrong and I do not know which result I can rely on. This is what I did in R library(mirt) #load(file="u3.RData")

Hey people, I''m starting a new project and just finished creating the ERM diagram with about 30 tables. There are quite some tables with foreign keys so I''m not sure how to start creating the controllers/models. How should I start creating controllers/models? Should I first create all tables without foreign key? Should I just start somewhere and add them radomly? I''m

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

Hello, Would someone have ever heard or developed any Item Response Models library for R ? Of course, a Rasch model can be estimated through glm() but it is not the case for more complex (polytomous) response models. Similarly I would be interested in any R implementation of nonlinear multivariate analyses a la GIFI (HOMALS, PRINCALS, OVERALS). Thanks a lot in advance, Yvonnick Noel, PhD.

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

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

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

Hello all, I have just started using fitting the PCM (Partial Credit Model) using eRm and have 2 problems which I cannot solve, I have checked everywhere on the net, but no joy: Firstly, I have fit a PCM model to 10 variables with differing response categories (3 for the first 6 items, 4 for the following 2 and 2 for the last two items). mat1 <- matrix(c(rasch_bart$bart_bowel,

I have constructed the function mml2 (below) based on the likelihood function described in the minimal latex I have pasted below for anyone who wants to look at it. This function finds parameter estimates for a basic Rasch (IRT) model. Using the function without the gradient, using either nlminb or optim returns the correct parameter estimates and, in the case of optim, the correct standard