Given an internal mirt object extracted from an estimated model, or the single-group estimated model itself, compute the probability trace lines for all categories.
probtrace(x, Theta)either an extracted internal mirt object containing item information
(see extract.item) or a model of class SingleGroupClass
typically returned by the function mirt or bfactor
a vector (unidimensional) or matrix (unidimensional/multidimensional) of latent trait values
Chalmers, R., P. (2012). mirt: A Multidimensional Item Response Theory Package for the R Environment. Journal of Statistical Software, 48(6), 1-29. doi:10.18637/jss.v048.i06
mod <- mirt(Science, 1)
# single item probabilty tracelines for Item 2
extr.2 <- extract.item(mod, 2)
Theta <- matrix(seq(-4,4, by = .1))
traceline <- probtrace(extr.2, Theta)
head(data.frame(traceline, Theta=Theta))
#> P.1 P.2 P.3 P.4 Theta
#> 1 0.8786646 0.1033965 0.01717048 0.0007684150 -4.0
#> 2 0.8649759 0.1147928 0.01936274 0.0008685506 -3.9
#> 3 0.8500065 0.1271837 0.02182811 0.0009817226 -3.8
#> 4 0.8336966 0.1405950 0.02459876 0.0011096245 -3.7
#> 5 0.8159972 0.1550385 0.02771018 0.0012541689 -3.6
#> 6 0.7968730 0.1705082 0.03120137 0.0014175155 -3.5
# probability tracelines for all items in test
tracelines <- probtrace(mod, Theta)
head(tracelines)
#> Comfort.P.1 Comfort.P.2 Comfort.P.3 Comfort.P.4 Work.P.1 Work.P.2
#> [1,] 0.3324476 0.4891306 0.1748568 0.003564956 0.8786646 0.1033965
#> [2,] 0.3097452 0.4960477 0.1902523 0.003954823 0.8649759 0.1147928
#> [3,] 0.2879244 0.5010453 0.2066432 0.004387139 0.8500065 0.1271837
#> [4,] 0.2670460 0.5040571 0.2240304 0.004866481 0.8336966 0.1405950
#> [5,] 0.2471562 0.5050429 0.2424030 0.005397913 0.8159972 0.1550385
#> [6,] 0.2282864 0.5039894 0.2617372 0.005987029 0.7968730 0.1705082
#> Work.P.3 Work.P.4 Future.P.1 Future.P.2 Future.P.3 Future.P.4
#> [1,] 0.01717048 0.0007684150 0.9809133 0.01813820 0.0009339072 1.456036e-05
#> [2,] 0.01936274 0.0008685506 0.9761110 0.02269637 0.0011743453 1.831346e-05
#> [3,] 0.02182811 0.0009817226 0.9701371 0.02836330 0.0014765907 2.303394e-05
#> [4,] 0.02459876 0.0011096245 0.9627263 0.03538820 0.0018564770 2.897114e-05
#> [5,] 0.02771018 0.0012541689 0.9535646 0.04406509 0.0023338620 3.643864e-05
#> [6,] 0.03120137 0.0014175155 0.9422860 0.05473458 0.0029336324 4.583085e-05
#> Benefit.P.1 Benefit.P.2 Benefit.P.3 Benefit.P.4
#> [1,] 0.7372533 0.2300751 0.03036097 0.002310633
#> [2,] 0.7155002 0.2481850 0.03373746 0.002577309
#> [3,] 0.6926969 0.2669559 0.03747256 0.002874673
#> [4,] 0.6689116 0.2862818 0.04160042 0.003206237
#> [5,] 0.6442308 0.3060358 0.04615750 0.003575906
#> [6,] 0.6187588 0.3260706 0.05118258 0.003988026