similar to: eRm: new version 0.9-6

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,

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")

I've defined the following for objects of a class called jml summary.jml <- function(object, ...){ tab <- cbind(Estimate = coef(object), StdError = object$se, Infit = object$Infit, Outfit = object$Outfit) res <- list(call = object$call, coefficients = tab, N = nrow(object$Data), iter = object$Iterations) class(res) <- "summary.jml" res }

I'm performing item response theory with eRm packages I am excluding the persons that doesn't fit in the infit/outfit persons. for that I created a condition. then I have to create a new subset or matrix but with the condition. So: ORIGINAL matrix<-cbind(item1, item2, item3, item4) IF I PERFORM A head(matrix) item1 item2 item3 item4 3 2 3 1 3 1

I have just submitted MiscPsycho to CRAN. MiscPsycho contains functions for miscellaneous psychometrics that may be useful for applied psychometricians. MML estimation already exists in the ltm package. Hence, a jml option is provided for users who prefer this method. The jml function gives back rasch difficulties and the same Infit and Outfit statistics as Winsteps. Also, jml is known to return

I have just submitted MiscPsycho to CRAN. MiscPsycho contains functions for miscellaneous psychometrics that may be useful for applied psychometricians. MML estimation already exists in the ltm package. Hence, a jml option is provided for users who prefer this method. The jml function gives back rasch difficulties and the same Infit and Outfit statistics as Winsteps. Also, jml is known to return

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 <-

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

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

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 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

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'm using the fwdmsa package to identify deviant cases in a Mokken scale analysis. I've run into a problem. When I use scales comprising a few items, iI tend to get an error: Error in y[order(res[-msamp])][1:(length(samp) + 1 - length(msamp))] : only 0's may be mixed with negative subscripts I understand that the error is triggered when the algorithm is fetching cases to enter

I am attempting to fit a partial credit model using the PCM() function in eRm. My data set comprises 88 items in 43 individuals with possible scores 0,1,2,3. Attempting either a PCM or RSM model fit simply hangs - no error messages but no return to command prompt and a continuously spinning "work in progress" indicator. The scores are from an instrument whose relevant psychometrics

Dear R-users, I'd like to announce the release of the new version of package `ltm' (i.e., ltm_0.8-0 soon available from CRAN) for Item Response Theory analyses. This package provides a flexible framework for analyzing dichotomous and polytomous data under IRT, including the Rasch model, the Two-Parameter Logistic model, Birnbaum's Three-Parameter model, the Latent Trait model

Dear R-users, I'd like to announce the release of the new version of package `ltm' (i.e., ltm_0.8-0 soon available from CRAN) for Item Response Theory analyses. This package provides a flexible framework for analyzing dichotomous and polytomous data under IRT, including the Rasch model, the Two-Parameter Logistic model, Birnbaum's Three-Parameter model, the Latent Trait model