search for: irte

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)

Hi, Is it possible to create a ts() object, whose data is daily based BUT measured only on working days? In other words, suppose I have a data set with 255 observations, measured from 29 June 1959 to 30 June 1960. How would I create such a data? I tried something like: ts(c(...), start(1959, 180)) but I'm not sure what to use for frequency. In other words I don't know how to

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 users, I'm a newby to R (and programming software at large) and I would need some help to sum up event data at discreet time and irregular time interval into a hourly frequency. Here is an example of my time series frame (irregular time-serie object - irts in the tseries package): time value 2008-12-19 19:11:03 GMT 1 2008-12-19 19:12:00 GMT 0 2008-12-19

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

I make quite a lot of use of irregular time-series, and had already spent a bit of time writing an 'its' class when the 'irts' class was released via the package 'tseries'. I have experimented with the 'irts' class, and have some practical issues with its use. In some applications of irregular time-series (in my case these are financial and econometric) there are

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

Hi R-list, I'm working with irregular time series (time series of climate data, daily data 365/6 days a year) and would like to create regular time series from them ( irts e.g. Rain <- irts(as.POSIXct(Climate[,1]),Climate[,5]) to ts e.g. test <- ts(x, start=c(1997,1), frequency=365) ) such that I can find where the gaps (lacking temperature data, ...) are and try

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

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(

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

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:

Hello, I want to compute Wainer et al's augmented subscore(2001) using IRT but I can't find any packages or relevant code. There is a 'subscore' package in R, but I think it only gives functions to calculate augmented subscores using CTT(classical test theory). Is there other package or code to compute subscores using IRT? If it is not, is there any plan to develop it in

Hi All, I have a data set of daily measurements of river flow. I would like to create a "ts" object from this data. Here's a sample data set: date <- as.Date(c(1:300), format="%Y") year=as.numeric(format(date, format = "%Y")) month=as.numeric(format(date, format = "%m")) julianday=as.numeric(format(date, format = "%j"))

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: 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

Hello R: i work on an IRT simulation research. I've written a code to generate a single dataset.As i will repeat simulating the data 100 times under every condition, how can i write the R code to make it run the single simulation code 100 times and save the generate results each time? Thanks so much~

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