similar to: differential item function for item response theory

Hi my friends, I have an issue with ability estimates when running GRM of IRT. I have responses from 242 subjects but got 183 ability estimates. Below is what I did to get the estimates. 1) I have a csv file "P1.csv" and I imported it into R and loaded the "ltm" package by doing: p1<-read.table("P1.csv",header=TRUE,sep=",") library(ltm) 2) I

Using the grm function (graded response IRT model) in the ltm package I receive the following error: Error: subscript out of bounds for several scales I'd like to examine. Here's a small example that if run a few times will likley produce the error at least once ch<-array(round(runif(50,1,5)),c(10,5)) grm(ch,start.val="random") ## or

I am using 32 bit R - 2.15.2 version and working on package ltm. The program does not give me any warning message when I run tpm command for a dataset. If run tpm command for the same dataset in 64-bit R 2.15.1 version, I get the warning message shown below. Can someone suggest why is no warning message being generated by 32-bit R? Or is it being generated but not getting printed? Which function

Afternoon R help, I want to run Rasch/IRT analyses using the ltm package, however, I am using large scale survey data which requires weighting for accurate results. I attempted to create a weighted object to insert into the formulae of the ltm packages, however, the survey data only includes 30 replicate weights and a sampling weight. The svrepdesign requires additional information such as

hello R: we have a two-parameter IRT simulation code. The goal is to generate a response matrix.But the "for" part doesn't run. we don't know what is wrong with it. Thanks so much~~~ I <- 10 J <- 5 response <- matrix(0, 10, 5) pij <- function(a,b,theta) { a <- rnorm(J, 0.8, 0.04) a b <- rnorm(J, 0, 1) b theta <- rnorm(I, 0,1) theta for( i in 1:I ) { for(

Hello All, I was wondering how I can get the overall Pearson chi^2 test of model fit with its df and p value in the LTM package for the 2PL models. Thanks, -- Davood Tofighi Department of Psychology Arizona State University [[alternative HTML version deleted]]

The function factor.scores is used with package ltm and others to estimate IRT type scores for various models. It inherits objects of class grm, gpcm and a few others. What I would like to do is to use the factor.scores function, but feed it my own item parameters (from a bifactor model where the 2PL parameters are adjusted for the bifactor structure). Does anybody have an idea of how this might

Hello All, I'm trying to print specific row and column for Observed_Scores matrix, however, when I execute the command "Observed_Scores[1,1]", I get the message "Error in Observed_Scores[1, 1] : incorrect number of dimensions". Could you please help and let me know where is the mistake? Here is my program: library(ltm) library(psych) # Settting the working directory

Hi all, Could anyone tell me if there is some package that fits any Item Response Model (further the ltm package)? Regards, Caio --------------------------------- [[alternative HTML version deleted]]

Hi Everybody, I have just been introduced to R and have used the ltm package for calibrating items under IRT. I have been able to get the item parameters using the fit function under different models. I am using the 2PL model. I have got the parameters for some 300 items from 15 different tests using the function fit. Now I need to automatically generate tests such that they have atleast a

Hi All, I'm generating 10 different data sets with 1 and 0 in a matrix form and writing the output in separate files. Now I need to stack all these data sets in one vector and I know that stack only operates on list or data frame however I got these data sets by converting list to a matrix so can't go backwards now. Is there a way i can still use Stack? Please see the program:

Dear all, I am trying to optimize a logistic function using optim, inside the following functions: #Estimating a and b from thetas and outcomes by ML IRT.estimate.abFromThetaX <- function(t, X, inits, lw=c(-Inf,-Inf), up=rep(Inf,2)){ optRes <- optim(inits, method="L-BFGS-B", fn=IRT.llZetaLambdaCorrNan, gr=IRT.gradZL, lower=lw, upper=up, t=t, X=X)

R glmmADMB question I am trying to use glmm.admb (the latest alpha version from the R forge website 0.6.4) to model my count data that is overdispersed using a negative binomial family but keep getting the following error message: Error in glmm.admb(data$total_bites_rounded ~ age_class_back, random = ~food.dif.id, : Argument "group" must be a character string specifying the

In the near future I will release MiscPsycho, a package that contains various functions useful for applied psychometricians. I would like to include some data sets for distribution in the package, but have not created any of these on my own, but have used data distributed in other packages such as the LSAT data in the ltm package. Is it appropriate for me to distribute a data set in the package I

Hello forum, I have developed an IRT model for a set of items on a large reference sample. I now want to use the IRT parameters that were estimated in the reference sample to score new individuals, one at a time. What R package(s) would allow me to do this? Also, several covariates were associated with item thresholds in the reference sample, so I was wondering if any programs can take

Hai, Can anyone help me with some literature (R related) about latent models? Thanx, Wilfred

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

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,

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