simulate_testbank: Simulate alpha and beta

In Karel-Kroeze/ShadowCAT: Multidimensional Computer Adaptive Testing with the Shadow Testing Procedure

Description

Simulate quick and simple itembanks.

Usage

simulate_testbank(model, number_items = 50, number_dimensions = 1,
  number_itemsteps = 4, items_load_one_dimension = FALSE,
  varying_number_item_steps = FALSE, alpha_bounds = c(0.3, 1.5))

Arguments

model	Model for which the item bank should be simulated. One of "3PLM", "GPCM", "SM" or "GRM", for the three-parameter logistic, generalized partial credit, sequential or graded response model respectively. If model is 3PLM, number of item steps is forced to 1.
number_items	Number of items.
number_dimensions	Number of dimensions of theta.
number_itemsteps	Number of item steps (number of categories minus 1); forced to 1 if model is 3PLM.
items_load_one_dimension	If TRUE, force items to load on one dimension each.
varying_number_item_steps	If TRUE, some item steps are set to NA; in this case number_itemsteps is the maximum number of itemsteps.
alpha_bounds	Vector containing lower and upper bound, respectively, of the uniform distribution from which the alpha values are drawn.

Value

Named list containing simulated alpha and beta matrix.

Examples

simulate_testbank(model = "GPCM", number_items = 50, number_dimensions = 2, number_itemsteps = 3)
simulate_testbank(model = "GPCM", number_items = 50, number_dimensions = 3, number_itemsteps = 4, 
                  items_load_one_dimension = TRUE, varying_number_item_steps = TRUE)

Karel-Kroeze/ShadowCAT documentation built on May 7, 2019, 12:28 p.m.