generate_testlet: Generate a random Testlet object

In irt: Item Response Theory and Computerized Adaptive Testing Functions

Generate a random Testlet object

Description

Generate a random Testlet object

Usage

generate_testlet(
  model = "BTM",
  n = NULL,
  item_models = "3PL",
  item_id_preamble = NULL,
  n_categories = 4,
  ...
)

Arguments

model	The model of the Testlet
n	The number of items in the Testlet.
item_models	A single model name or a vector of model names with the size of n that represents the models of items in the Testlet object.
item_id_preamble	The preamble for the item ids within the Testlet.
n_categories	For polytomous items, designate the number of categories each item should have. It can be a single integer value larger than 1. In this case all of the polytomous items of the testlet will have this number of categories. It can be a vector of length n designating the categories of each item. For dichotomous items, the values in n_categories will be ignored.
...	Additional parameters passed to testlet() function.

Value

A Testlet-class object

Author(s)

Emre Gonulates

Examples

# By default, a Testlet object with '3PL' model items generated
generate_testlet()
# Designate the number of items in the testlet
generate_testlet(n = 12)
# Set the ID of the testlet
generate_testlet(testlet_ = "my-testlet")
# Designate the ID of testlet and preamble for item ids
generate_testlet(testlet_id = "my-testlet", item_id_preamble = "mt-")
# Generate item pools for other models
generate_testlet(item_model = "Rasch")
generate_testlet(item_model = "1PL")
generate_testlet(item_model = "2PL")
generate_testlet(item_model = "4PL")
generate_testlet(item_model = "GRM") # Graded Response Model
generate_testlet(item_model = "GPCM") # Generalized Partial Credit Model
generate_testlet(item_model = "PCM") # Partial Credit Model
generate_testlet(item_model = "GPCM2") # Reparameterized GPCM
# Mixture of models
generate_testlet(item_models = c("4PL", "Rasch"))
generate_testlet(model = c("2PL", "GRM", "Rasch"), n = 11)

# Generating multiple testlet objects with custom ids
sapply(paste0("testlet-", 1:4), function(x) generate_testlet(testlet_id = x))

# Generate testlet with dichotomous and polytomous with different number of
# categories.
generate_testlet(
  item_models = c("3PL", "GRM", "GPCM", "GRM", "2PL"),
  n_categories = c(2, 3, 6, 7, 2))

# # Generating multiple testlet objects with custom ids and item models and
# # put them in an item pool:
# temp_list <- list(ids = paste0("testlet-", 1:3),
#                   item_models = c("Rasch", "2PL", "GPCM"))
# itempool(sapply(1:length(temp_list$item_id), function(i)
#   generate_testlet(item_id = temp_list$item_id[i],
#   item_models = temp_list$item_models[i])))

irt documentation built on Nov. 10, 2022, 5:50 p.m.