TestDesign (version 1.7.0)

Shadow: Run adaptive test assembly

Description

Shadow is a test assembly function for performing adaptive test assembly based on the generalized shadow-test framework.

Usage

Shadow(
  config,
  constraints = NULL,
  true_theta = NULL,
  data = NULL,
  prior = NULL,
  prior_par = NULL,
  exclude = NULL,
  include_items_for_estimation = NULL,
  force_solver = FALSE,
  session = NULL,
  seed = NULL,
  cumulative_usage_matrix = NULL
)
# S4 method for config_Shadow
Shadow(
  config,
  constraints = NULL,
  true_theta = NULL,
  data = NULL,
  prior = NULL,
  prior_par = NULL,
  exclude = NULL,
  include_items_for_estimation = NULL,
  force_solver = FALSE,
  session = NULL,
  seed = NULL,
  cumulative_usage_matrix = NULL
)

Value

Shadow returns an output_Shadow_all object containing assembly results.

Arguments

config

a config_Shadow object. Use createShadowTestConfig for this.

constraints

a constraints object representing test specifications. Use loadConstraints for this.

true_theta

(optional) true theta values to use in simulation. Either true_theta or data must be supplied.

data

(optional) a matrix containing item response data to use in simulation. Either true_theta or data must be supplied.

prior

(optional) density at each config@theta_grid to use as prior. Must be a length-nq vector or a nj * nq matrix. This overrides prior_dist and prior_par in the config. prior and prior_par cannot be used simultaneously.

prior_par

(optional) normal distribution parameters c(mean, sd) to use as prior. Must be a length-nq vector or a nj * nq matrix. This overrides prior_dist and prior_par in the config. prior and prior_par cannot be used simultaneously.

exclude

(optional) a list containing item names in $i and set names in $s to exclude from selection for each participant. The length of the list must be equal to the number of participants.

include_items_for_estimation

(optional) an examinee-wise list containing:

• administered_item_pool items to include in theta estimation as item_pool object.

• administered_item_resp item responses to include in theta estimation.

force_solver

if TRUE, do not check whether the solver is one of recommended solvers for complex problems (set-based assembly, partitioning). (default = FALSE)

session

(optional) used to communicate with Shiny app TestDesign.

seed

(optional) used to perform data generation internally.

cumulative_usage_matrix

(optional) a *nj* by (*ni* + *ns*) matrix containing the number of times the item/stimulus was administered previously to each participant. Stimuli representations are appended to the right side of the matrix.

References

van der Linden, W. J., Reese, L. M. (1998). A model for optimal constrained adaptive testing. Applied Psychological Measurement, 22, 259-270.

van der Linden, W. J. (1998). Optimal assembly of psychological and educational tests. Applied Psychological Measurement, 22, 195-211.

van der Linden, W. J. (2000). Optimal assembly of tests with item sets. Applied Psychological Measurement, 24, 225-240.

van der Linden, W. J. (2005). Linear models for optimal test design. Springer Science & Business Media.

Examples

config <- createShadowTestConfig()
true_theta <- rnorm(1)
solution <- Shadow(config, constraints_science, true_theta)
solution@output