similar to: ltm package question

Dear R-List, to assess the model fit for 2PL-models, I tried to mimic the bootstrap-approach chosen in the GoF.rasch()-function. Not being a statistician, I was wondering whether the following simplification (omit the "chi-squared-expressed model fit-step") would be appropriate: GoF.ltm <- function(object, B = 50, ...){ liFits <- list() for(i in 1:B){ rndDat <-

Hello, II used the logLik() function to get the log-likelihood estimate of an object. The function also prints the degrees of freedom. How can I extract the degrees of freedom and assign it to a variable. Below is the output: > logLik(fit2pl) 'log Lik.' -4842.912 (df=36) Thanks, Davood Tofighi [[alternative HTML version deleted]]

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,

Hola a todos, Os envío una consulta que considero sencilla pero me está resultando imposible de resolver. Si ejecutáis el siguiente código, obtendréis la gráfica que os adjunto: library(ltm) modelo <- rasch(LSAT) plot(modelo, main="Curva probabilidad pregunta 1",legend = TRUE, cx = "bottomright", items=1,xlab="Conocimiento",ylab="Probabilidad") Resulta

Dear All, I am running a Monte Carlo simulation study and have some questions on how to manage data storage efficiently at the end of each 1000 replication loop. I have three conditions coded using the FOR {} loops and a FOR loop that generates data for each condition, performs analysis, and computes a statistic 1000 times. Therefore, for each condition, I will have 1000 statistic values. My

Dear All, I have a function f(x,y,z)=exp(x^3+y^4+x^2*y+x*z^2+y/z) over D, where is D={ (x,y,z)| 0 <z<Inf, 0<y<c1*z, 0<x<c2*/y}. x,y,z are all vectors and c1 and c2 are constants. I tried the "adapt" package and I get some error. This is the error message: "Error in function (z, y, x) : argument "x" is missing, with no default" I included my R

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, I'm using filehash on the windows XP and it has been working fine with the newest R version 2.6.2. However, on the windows vista, when I ran the same code, I got the following error: > dbCreate("simdb") #create simdb database [1] TRUE > db<-dbInit("simdb") #initiate an object of database Error in sprintf(gettext(fmt, domain = domain), ...) : object

Hola a todos, Estoy usando la librería ltm, de teoría de respuesta al ítem, para crear gráficos. Resulta que añado unas líneas horizontales en los valores de 0.25, 0.50 y 0.75. Me gustaría que en el gráfico, desaparezcan las marcas de 0,.2, 0.4, 0.6 y 0.8 y aparezcan en 0.25, 0.50 y 0.75. He probado varias cosas que he visto por Googe pero no me han funcionado. ¿Alguna idea? library(ltm) # creo el

Dear Listers: I used cronbach{psy} to evaluate the internal consistency and some set of variables gave me alpha=-1.1003, while other, alpha=-0.2; alpha=0.89; and so on. I am interested in knowing how to interpret 1. negative value 2. negative value less than -1. I also want to re-mention my previous question about how to evaluate the consistency of a set of variables and about the total

Hello, I will use the lca method in the e1071 package. But I get the following error: Error in pas[j, ] <- drop(exp(rep(1, nvar) %*% log(mp))) : number of items to replace is not a multiple of replacement length Does anybody know this error and knows what this means? Kind regards, Tryntsje

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]]

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

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

Mando este mensaje de respuesta para dar las gracias tanto a Pedro como a Carlos por sus sugerencias. Ahora ya tengo los números que quiero en la gráfica, me falta por quitar los que no quiero. Teniendo en cuenta lo que dice Pedro, voy a preguntar al autor de la librería. saludos, Fernando En martes, 9 de octubre de 2018 13:23:51 CEST, Carlos Ortega <cof en qualityexcellence.es>

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

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

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

Hello! I am running a very simple mini Monte-Carlo below using the function tstatistic (right below this sentence): tstatistic = function(x,y){ m=length(x) n=length(y) sp=sqrt( ((m-1)*sd(x)^2 + (n-1)*sd(y)^2)/(m+n-2) ) t=(mean(x)-mean(y))/(sp*sqrt(1/m+1/n)) return(t) } alpha=.1; m=10; n=10 # sets alpha, m, n - for run 1 N=10000 # sets the number of simulations n.reject=0 # counter of num.

Here's one possibility, assuming muhat and sigmahat are estimtes of mu and sigma from N iid draws of N(mu, sigma^2): tStat <- abs(x - muhat) / sigmahat pValue <- pt(tStat, df=N, lower=TRUE) I'm not quite sure what df tStat should have (exercise for math stat), but given fairly large N, that should make little difference. Andy > From: Ross Clement > > Hi. I have a