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R/boot.mirt.R

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#' plot(booted)
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#' booted
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#'
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#' \dontrun{
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#' #run in parallel using snow back-end using all available cores
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#' mod <- mirt(Science, 1)
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#' booted <- boot.mirt(mod, parallel = 'snow', ncpus = parallel::detectCores())
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#' booted
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#' }
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#'
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#' ####
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#' # bootstrapped CIs for standardized factor loadings

R/itemGAM.R

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#' dat <- dat[,-32]
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#' mod <- mirt(dat, 1)
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#'
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#' \dontrun{
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#' # Kernal smoothing is very sensitive to which category is selected as 'correct'
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#' # 5th category as correct
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#' ks <- ksIRT(cbind(dat, SAT12[,32]), c(rep(1, 31), 5), 1)
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#' # 3rd category as correct
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#' ks <- ksIRT(cbind(dat, SAT12[,32]), c(rep(1, 31), 3), 1)
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#' plot(ks, items = c(1,2,32))
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#' }
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#'
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#' # splines approach
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#' Theta <- fscores(mod)

man/boot.mirt.Rd

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man/itemGAM.Rd

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