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Hi, Phil, In my study I am thinking of using mirt function for calibrating mixed format multidimensional data. In mirt manual, I couldn't figure out the theoretical background of this analysis. Which models it used, Could you provide the names of articles that form the base of the analysis. I need it for Methods section of the study
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Hi Mr Chalmers:The following codes were provided by you a couple months ago.> #simulated dichotomous items first, slopes at 1, with simple structure> d <- matrix(rnorm(80))> a <- matrix(c(rep(1, 40), rep(0,80), rep(1,40)), 80)> dichitems <- simdata(a, d, 1000, Theta=Theta, itemtype = 'dich')>> #now graded items, with 5 categories each> a2 <- matrix(c(rep(1, 20), rep(0,40), rep(1,20)), 40)> d2 <- matrix(rnorm(40*4), 40)> d2 <- t(apply(d2, 1, sort, decreasing=TRUE)) #sort since intercepts are ordered> polytomous <- simdata(a2, d2, 1000, Theta=Theta, itemtype = 'graded')>> dat <- data.frame(dich=dichitems, poly=polytomous)>> #estimate it> model <- mirt.model('F1 = 1-40, 81-100+ F2 = 41-80, 101-120+ COV = F1*F2')> mod <- mirt(dat, model)They were working great at that time but ,currently, it is not working and give the following message
Error message: FUN(newX[, i], ...) :Items contain category scoring spaces greater than 1.Use apply(data, 2, table) to inspect and fixWhat could be the probable reason for that,Additionally, as I know plink package is not available currently so, read.mirt function is useless. I download an older version of plink (version 1.3.1) is there any way to use parameters from mirt to use in plink other than managing the matrices.
One last question, is that when running the above codes the following coeffs given$dich.Item_1a1 a2 d g upar 0.99 0 -0.843 0 1$dich.Item_2a1 a2 d g upar 1.011 0 -0.34 0 1(I add a few lines). Why a2 parameters are always estimated zero. is it related to producing "a" matrix(a <- matrix(c(rep(1, 40), rep(0,80), rep(1,40)), 80))I couldn't control it because of the error mentioned above...
I would be glad for your contributionBest!Kif
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