The tmt Package provides conditional maximum likelihood (CML) estimation of item parameters in multistage designs (Zwitser & Maris, 2013, https://doi.org/10.1007/s11336-013-9369-6) and CML estimation for conventional designs. Additional features are the Likelihood Ratio test (Andersen, 1973, https://doi.org/10.1007/BF02291180) and simulation of multistage designs.
To install the development version of the tmt package, please copy this commands in your R console:
# Install release version from CRAN
install.packages("tmt")
# Install development version from GitHub
devtools::install_github("jansteinfeld/tmt")You will find a detailed description of the package in the vignette:
library(tmt)
mstdesign <- "
M1 =~ paste0('i',1:5)
M2 =~ c(i6, i7, i8, i9, i10)
M3 =~ c(i11, i12, i13, i14, i15)
M4 =~ c(i16, i17, i18, i19, i20)
M5 =~ c(i21, i22, i23, i24, i25)
M6 =~ c(i26, i27, i28, i29, i30)
# define starting module
Start == M4
# define branches
p1 := Start(0,2) + M2(0,2) + M1(0,5)
p2 := Start(0,2) + M2(3,5) + M3(0,5)
p3 := Start(3,5) + M5(0,2) + M3(0,5)
p4 := Start(3,5) + M5(3,5) + M6(0,5)
"
# simulate some data
items <- seq(-2,2,length.out=30)
names(items) <- c(paste0("i",1:30))
set.seed(1111)
dat_mst <- tmt_sim(mstdesign = mstdesign,
items = items,
persons = 500,
mean = 0,
sd = 1)
# estimate
mod1 <- tmt_rm(dat_mst,mstdesign = mstdesign)
summary(mod1)
#>
#> Call:
#> tmt_rm(dat = dat_mst, mstdesign = mstdesign)
#>
#>
#> Results of Rasch model (mst) estimation:
#>
#> Difficulty parameters:
#> est.b_i1 est.b_i2 est.b_i3 est.b_i4 est.b_i5 est.b_i6
#> Estimate -1.715056 -1.6100686 -1.508108 -1.6100686 -1.3113453 -1.0468543
#> Std. Error 0.247141 0.2439233 0.241220 0.2439233 0.2371614 0.1520214
#> est.b_i7 est.b_i8 est.b_i9 est.b_i10 est.b_i11
#> Estimate -1.1508557 -0.9958313 -0.6997328 -0.4607495 -0.3807713
#> Std. Error 0.1535503 0.1513333 0.1480823 0.1464329 0.1326975
#> est.b_i12 est.b_i13 est.b_i14 est.b_i15 est.b_i16
#> Estimate -0.6500487 -0.222511 -0.2082786 -0.05286967 0.07542945
#> Std. Error 0.1359553 0.131522 0.1314425 0.13085158 0.11053665
#> est.b_i17 est.b_i18 est.b_i19 est.b_i20 est.b_i21 est.b_i22
#> Estimate 0.2472522 0.3046942 0.5762328 0.5959613 0.7193856 0.5738666
#> Std. Error 0.1108281 0.1109871 0.1121476 0.1122602 0.1668250 0.1662375
#> est.b_i23 est.b_i24 est.b_i25 est.b_i26 est.b_i27 est.b_i28
#> Estimate 0.8659746 1.0363980 1.1895060 1.401457 1.401457 1.2465019
#> Std. Error 0.1677771 0.1693014 0.1710693 0.245725 0.245725 0.2450162
#> est.b_i29 est.b_i30
#> Estimate 1.5586564 1.830376
#> Std. Error 0.2475203 0.253225
#>
#> CLL: -3222.077
#> Number of iterations: 59
#> Number of parameters: 30The following features are planned for future releases: