This function simulates data according to the specified and submitted multistage design. The persons are drawn from a standard normal distribution if the amount of persons are specified. As an additional argument, a seed can also be set. If requested, it is also possible to submit a vector ore list of person parameters to specify different person distributions.
tmt_sim(
mstdesign = NULL,
items = NULL,
persons = NULL,
preconditions = NULL,
...
)definition of desired multistage design
vector of difficulty parameters for each items
amount of persons per starting module
definition of preconditions can optionally be specified. In the case of probabilistic routing preconditions such as a pre-test, which are taken into account in the MST design. For the specification the correlation with the true person parameter have to be specified. The submitted correlation is adjusted in the function according to Demirtas and Yavuz (2015; <doi:10.1080/10543406.2014.920868>) It is also possible to submit your own vector with integers for the preconditions.
further optional arguments like setting a seed
List with following entries
Matrix with item responses
Data frame with item responses and additional a vector of used modules per person
Generated and used person parameters
Submitted multistage design
Demirtas, H., & Yavuz, Y. (2015). Concurrent Generation of Ordinal and Normal Data. Journal of Biopharmaceutical Statistics, 25(4), 635-650. https://doi.org/10.1080/10543406.2014.920868
#############################################################################
# translate multistage model 1
#############################################################################
mstdesign <- "
M1 =~ c(i1, i2, i3, i4, i5)
M2 =~ c(i6, i7, i8, i9, i10)
M3 =~ c(i11, i12, i13, i14, i15)
# define branches
p1 := M2(0,2) + M1
p2 := M2(3,5) + M3
"
items <- seq(-3,3,length.out = 15)
names(items) <- paste0("i", seq(items))
data_1 <- tmt_sim(mstdesign = mstdesign,
items = items,
persons = 500,
seed = 1111)
#############################################################################
# translate multistage model 2
#############################################################################
mstdesign <- "
M1 =~ c(i1, i2, i3, i4, i5)
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 branches
p1 := M4(0,2) + M2(0,2) + M1
p2 := M4(0,2) + M2(3,5) + M3
p3 := M4(3,5) + M5(0,2) + M3
p4 := M4(3,5) + M5(3,5) + M6
"
items <- seq(-3,3,length.out = 30)
names(items) <- paste0("i", seq(items))
data_2 <- tmt_sim(mstdesign = mstdesign,
items = items,
persons = 500,
seed = 1111)