similar to: IRT simulation repeated

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 R, I am looking for non-parametric simulation in IRT. Is there any IRT package that does non-parametric simulation? helen L [[alternative HTML version deleted]]

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

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)

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

Dear all members, I am Phd. candidate student at Chulalongkorn U., Thailand. I am interested in expectation maximization algorithm (EM) and multiple imputation (MI) for imputation missing values(missing at random(MAR) and missing not at random (MNAR)) in IRT (3-PL). So, I want to know about package in R or function of EM and MI for simulate this problem I am looking forward your answer.

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 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

Hi: I need to apply the IRT model from Ramsay (1991), He apply the Smoothing Kernel to multiple choice test. Is possible in R?. Thank you, Xavier G. Ordonez Doctoral Student Universidad Complutense de Madrid

Dear all, I?m doing some simulation studies in order to compare the estimates (and estimated standard deviations) from the ARMA(2,1) Model with an estimator that I?ve constructed. For carrying out the simulations I created a VBA project within Excel. Now, I?m using the RExcel tool for running the R commands in the VBA project. I run 2500 simulation using the ?arima? function from R and it worked!

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 Guy's I was wondering if someone could point me in the right direction. dbinom(10,1,0.25) I am using dbinom(10,1,0.25) to calculate the probabilty of 10 judges choosing a certain brand x times. I was wondering how I would go about simulating 1000 trials of each x value ? regards Brendan -- View this message in context:

The first version of the package plink has been uploaded to CRAN. plink is a package for conducting unidimensional IRT scaling and chain linking for multiple groups for single-format or mixed-format common items. The package supports eight IRT models and four calibration methods. Dichotomous Models: 1PL, 2PL, 3PL Polytomous Models: -Graded response model -Partial credit model -Generalized

The first version of the package plink has been uploaded to CRAN. plink is a package for conducting unidimensional IRT scaling and chain linking for multiple groups for single-format or mixed-format common items. The package supports eight IRT models and four calibration methods. Dichotomous Models: 1PL, 2PL, 3PL Polytomous Models: -Graded response model -Partial credit model -Generalized

Hello, I am having really hard time finding a good article about simulating genotypes of cases and controls at a disease locus using R. if you guys can point me or guide me where i can find more information, it will be helpful. thanks, Claire -- View this message in context: http://www.nabble.com/genotypes-simulation-tp17065607p17065607.html Sent from the R help mailing list archive at

Dear R-users, I'm trying to do some spatial simulation. I have two covariates, Z and C. I want to examine their relationship under different spatial distribution. I have no problem simulating completely spatial random process but I'm totally stuck on poisson (cluster) pattern. I already have a dataset with Z and C (obs=575) and I know the relationship between them. Using these 575

Dear R Helpers, I have searched for any R package or code for simulating multivariate fractional Brownian motion (mFBM) or multivariate fractional Gaussian noise (mFGN) when a covariance matrix are given. Unfortunately, I could not find such a package or code. Can you suggest any solution for multivariate FBM and FGN simulation? Thank you for your help. Best Regards, Ryan ----- Wonsang You

Hello everyone, I have a question regarding simulating based on runif.? Let say I have generated matrix A and B based on runif. Then I find mean for each matrix A and matrix B.? I want this process to be done let say 10 times. Anyone can help me.? Actually I want make the function that I can play around with the number of simulation process that I want. Thanks. Eg: a <- matrix(runif(5,1, 10))

An updated version of the package plink has been uploaded to CRAN. This is a major revision that now includes multidimensional models and methods. plink is a package for conducting unidimensional and multidimensional IRT-based test linking using separate calibration methods for multiple groups for single-format or mixed-format common items. The package supports sixteen IRT models and eleven

An updated version of the package plink has been uploaded to CRAN. This is a major revision that now includes multidimensional models and methods. plink is a package for conducting unidimensional and multidimensional IRT-based test linking using separate calibration methods for multiple groups for single-format or mixed-format common items. The package supports sixteen IRT models and eleven