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eap-methods

Compute expected a posteriori estimates of theta

Description

eap is a function to compute expected a posteriori estimates of theta.

Usage

eap(
  object,
  select = NULL,
  resp,
  theta_grid = seq(-4, 4, 0.1),
  prior = rep(1/81, 81)
)

## S4 method for signature 'item_pool'
eap(
  object,
  select = NULL,
  resp,
  theta_grid = seq(-4, 4, 0.1),
  prior = rep(1/81, 81)
)

EAP(object, select = NULL, prior, reset_prior = FALSE)

## S4 method for signature 'test'
EAP(object, select = NULL, prior, reset_prior = FALSE)

## S4 method for signature 'test_cluster'
EAP(object, select = NULL, prior, reset_prior = FALSE)

Arguments

object

an item_pool object.
select

(optional) if item indices are supplied, only the specified items are used.
resp

item response on all (or selected) items in the object argument. Can be a vector, a matrix, or a data frame. length(resp) or ncol(resp) must be equal to the number of all (or selected) items.
theta_grid

the theta grid to use as quadrature points. (default = seq(-4, 4, .1))
prior

a prior distribution, a numeric vector for a common prior or a matrix for individualized priors. (default = rep(1 / 81, 81))
reset_prior

used for test_cluster objects. If TRUE, to reset the prior distribution before each test.

Value

eap returns a list containing estimated values.

  • th theta value.

  • se standard error.

Examples

eap(itempool_fatigue, resp = resp_fatigue_data[10, ])
eap(itempool_fatigue, select = 1:20, resp = resp_fatigue_data[10, 1:20])
TestDesign

Optimal Test Design Approach to Fixed and Adaptive Test Construction

v1.2.2
GPL (>= 2)
Authors
Seung W. Choi [aut, cre] (<https://orcid.org/0000-0003-4777-5420>), Sangdon Lim [aut] (<https://orcid.org/0000-0002-2988-014X>)
Initial release
2021-01-26

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