loadItemPool
is a data loading function for creating an item_pool
object.
loadItemPool
can read item parameters and standard errors from a data.frame
or a .csv file.
loadItemPool(ipar, ipar_se = NULL, unique = FALSE)
item parameters. Can be a data.frame
or the file path of a .csv file. The content should at least include columns 'ID' and 'MODEL'.
(optional) standard errors. Can be a data.frame
or the file path of a .csv file.
if TRUE
, item IDs must be unique to create a valid item_pool
object. (default = FALSE
)
loadItemPool
returns an item_pool
object.
ni
the number of items in the pool.
max_cat
the maximum number of response categories across all items in the pool.
index
the numeric item index of each item.
id
the item ID string of each item.
model
the object class names of each item representing an item model type.
Can be item_1PL
, item_2PL
, item_3PL
,
item_PC
, item_GPC
, or item_GR
.
NCAT
the number of response categories of each item.
parms
a list containing the item object of each item.
ipar
a matrix containing all item parameters.
se
a matrix containing all item parameter standard errors. The values will be 0 if the argument ipar_se
was not supplied.
raw
the original input ipar
argument used to create this object.
raw_se
the original input ipar_se
argument used to create this object.
If the argument was not supplied, this will be in the same structure with the ipar
argument but the item parameter values will be filled with 0s.
unique
the original input unique
argument used to create this object.
dataset_science
, dataset_reading
, dataset_fatigue
, dataset_bayes
for examples.
## Read from data.frame:
itempool_science <- loadItemPool(itempool_science_data)
## Read from file: write to tempdir() for illustration and clean afterwards
f <- file.path(tempdir(), "itempool_science.csv")
write.csv(itempool_science_data, f, row.names = FALSE)
itempool_science <- loadItemPool(f)
file.remove(f)
#> [1] TRUE