View source: R/generate_objects.R
generate_ip | R Documentation |
Itempool
objectGenerate a random Itempool
object
generate_ip(
model = "3PL",
n = NULL,
output = "Itempool",
n_categories = 4,
se = NULL,
...
)
model |
The model of the item pool |
n |
The number of items in the item pool. |
output |
The type of object returned. The default value is
|
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 will have this number of categories.
It can be a vector of length |
se |
The values of parameter standard errors for each item,
i.e. a list
object with elements named as parameter names (excluding If the value is |
... |
Additional parameters passed to |
An Itempool-class
object
Emre Gonulates
# By default, a '3PL' model item pool generated
generate_ip()
# Designate the number of items
generate_ip(n = 12)
# Generate item pools for other models
generate_ip(model = "Rasch")
generate_ip(model = "1PL")
generate_ip(model = "2PL")
generate_ip(model = "4PL")
generate_ip(model = "GRM") # Graded Response Model
generate_ip(model = "GPCM") # Generalized Partial Credit Model
generate_ip(model = "PCM") # Partial Credit Model
generate_ip(model = "GPCM2") # Reparameterized GPCM
# Mixture of models
generate_ip(model = c("4PL", "Rasch"))
generate_ip(model = sample(c("4PL", "GPCM"), 12, TRUE))
generate_ip(model = c("2PL", "GRM", "Rasch"), n = 11)
# Generate parameters standard errors for each item
generate_ip(se_paramters = TRUE)
# Generate an item pool consist of testlets and standalone items
temp_list <- list(ids = paste0("testlet-", 1:7), n = c(2, 3, 4, 2, 3, 4, 2))
ip <- itempool(sample(c(
generate_ip(n = 10, output = "list"),
sapply(1:length(temp_list$ids), function(i)
generate_testlet(testlet_id = temp_list$ids[i],
n = temp_list$item_models[i],
item_id_preamble = paste0("t", i, "-"))))))
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