similar to: 'R' library for Rasch modelling?

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

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 <-

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 am writing a small function to approximate an integral that cannot be evaluated in closed form. I am partially successful at this point and am experiencing one small, albeit important problem. Here is part of my function below. This is a psychometric problem for dichotomously scored test items where x is a vector of 1s or 0s denoting whether the respondent answered the item correctly (1) or

Dear List I apologize for the multiple postings. After being in the weeds on this problem for a while I think my original post may have been a little cryptic. I think I can be clearer. Essentially, I need the following a <- c(2,3) b <- c(4,5,6) (2*4) + (2*5) + (2*6) + (3*4) + (3*5) +(3*6) But I do not know of a built in function that would do this. Any suggestions? -----Original

This is a very basic question, but I am a bit confused with optim. I want to get the MLEs using optim which could replace the newton-raphson code I have below which also gives the MLEs. The function takes as input a vector x denoting whether a respondent answered an item correctly (x=1) or not (x=0). It also takes as input a vector b_vector, and these are parameters of test items (Rasch estimates

I'm creating a stacked bar chart using the likert command in the HH package. My data are in a data frame, with two numeric variables and a categorical variable, I can't get likert to use the column containing the categorical variable as a my y axis label. Here is a quick example: library(HH) #my data are:

R- Help Forum Working with the "likert" package and I can't figure out why my "bar" graphs are backwards (see attached). The percentages are place correctly but the bars are backwards. #Sample code # libraries library(likert) # create data band <- c("Band 3","Band 3","Band 3","Band 3","Band 3","Band

Hola a todos. Estoy intentando instalar el paquete likert utilizando devtools y obtengo el siguiente error library(devtools) install_github('likert','jbryer') Installing github repo(s) likert/master from jbryer Downloading likert.zip from https://github.com/jbryer/likert/archive/master.zip Error en function (type, msg, asError = TRUE) : <not set> Me pasa también con

Si. Pero no funciona. En ordenador curro si funciona y tb tiene linux. Seguiré investigando has probado con: install_github('paquete",username='usuario')? 2013/12/20 Jose Luis Cañadas Reche <canadasreche@gmail.com>: > Hola a todos. > > Estoy intentando instalar el paquete likert utilizando devtools y obtengo el > siguiente error > > library(devtools) >

Gracias Oscar. Funciona perfectamente. Ya investigaré más adelante porque no funciona install_github Saludos y feliza navidad.. El 20/12/13 23:05, Oscar Perpiñan escribió: > tmp <- paste0(tempdir(), '/likert.zip') > download.file('https://github.com/jbryer/likert/archive/master.zip', > destfile=tmp, method='wget') > unzip(tmp,

I'm testing an education assessment (evaluating quantitative skills in biology students) for reliability. I used cronbach's alpha, but got a really low alpha which I think is likely due to my small number of questions (12) and the fact that the questions are of varying difficulty. After a lot of reading, it looks like Rasch models are probably a more appropriate tool for my question so

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

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

Dear R members Could someone tell me how to simulate Likert-type data using the rnorm function. Let's say, 200*15 random numbers in a variable that goes from 1 to 4 in steps of 1 (i.e., 1, 2, 3, 4) belonging to a normal distribution? random.data <— matrix(rnorm(200 * 15), nrow = 200, ncol = 15) random.data The result cannot be reached. could one help me revise the syntax?

Hi, I have just found this forum, and it looks like a great place to get some help (I hope) For my dissertation, which is due way too soon, I am doing a survey, comparing attitudes of 2 independent groups, with 5 scale likert questions. Basically I want to show if they have similar or different attitudes. I am testing 4 hypotheses, and have in total about 20 questions. I have to say my

R- Help Forum Working with the "likert" package and find that my "bar" graphs are backwards (see attached) > summary(results) Item low neutral high mean sd 4 Q4 5 15 80 2.75 0.5501196 5 Q5 20 40 40 2.20 0.7677719 1 Q1 65 30 5 1.40 0.5982430 3 Q3 5 90 5 2.00 0.3244428 2 Q2 90 10 0 1.10 0.3077935

Hi everyone, I'm stuck on my dissertation which is due next week. I'm a business major student and my project is a comparative research on corporate social responsibility (CSR) between Chinese and German firms. According to my literature review, it's quite obvious that German firms have much better CSR initiatives and strategies than the Chinese ones and I wanted to test whether it was

I have a function that I am currently using very inefficiently. The following are needed to illustrate the problem: set.seed(12345) dat <- matrix(sample(c(0,1), 110, replace = TRUE), nrow = 11, ncol=10) mis <- sample(1:110, 5) dat[mis] <- NA theta <- rnorm(11) b_vector <- runif(10, -4,4) empty <- which(is.na(t(dat))) So, I have a matrix (dat) with some values within the matrix

in order to know which production the custumer most like,i design a question as follow : Q:there are six production listed below.according to your preference,the production you like most is_____,the production you secondly like is ____,and the third is_____. productionA productionB productionC productionD productionE productionF when the data is collected. i type in a