cat_sim_fast {irt} | R Documentation |
Computerized Adaptive Test (CAT) Simulation (Parallel Computing)
Description
cat_sim_fast
function simulates computerized adaptive test (CAT) for
one or many simulees. This function uses parallel computing, so, for large
number of simulees, it might be significantly faster than
cat_sim
function.
Usage
cat_sim_fast(true_ability, cd, verbose = -1, n_cores = NULL)
Arguments
true_ability |
True ability vector to generate item responses. |
cd |
A |
verbose |
This is an integer that will print the stage of the test.
For example, if the value verbose = 10, a message will be printed at
each tenth iteration of the cat_simulation. Default value is |
n_cores |
an integer specifying the number of cores to be used.
The value should be 1 or larger. The default is |
Value
If the length of true_ability
vector is one a
"cat_output"
class output will be returned.
This is a list containing following elements:
- true_ability
True ability (theta) value to generate item responses.
- est_history
A list where each element represent a step of the CAT test. It has following elements:
- est_before
The estimated ability before the administration of the item.
- se_before
The standard error of the estimated ability before the administration of the item.
- testlet
TRUE
if the item belongs to a testlet.- item
Item-class
object that is administered at this step.- resp
The simulated response of the simulee for the item administered at this step using simulee's
true_ability
value.- est_after
The estimated ability after the administration of the item.
- se_after
The standard error of the estimated ability after the administration of the item.
If the length of the true_ability
is more than 1, a list of
cat_output
objects will be returned for each value of
true_ability
.
Author(s)
Emre Gonulates
See Also
Examples
cd <- create_cat_design(ip = generate_ip(n = 30),
termination_rule = c('max_item'),
termination_par = list(max_item = 7))
cat_sim_fast(true_ability = rnorm(1), cd = cd, n_cores = 1)
cat_sim_fast(true_ability = rnorm(2), cd = cd, n_cores = 1)