JAJ: JAJ

In klausfrieler/JAJ: Jack & Jill Memory Test

JAJ

Description

This function defines a JAJ module for incorporation into a psychTestR timeline. Use this function if you want to include the JAJ in a battery of other tests, or if you want to add custom psychTestR pages to your test timeline. For demoing the JAJ, consider using JAJ_demo(). For a standalone implementation of the JAJ, consider using JAJ_standalone().

Usage

JAJ(
  num_items = 16L,
  take_training = TRUE,
  with_welcome = TRUE,
  with_finish = TRUE,
  label = "JAJ",
  feedback = JAJ::JAJ_feedback_with_score(),
  next_item.criterion = "bOpt",
  next_item.estimator = "BM",
  next_item.prior_dist = "norm",
  next_item.prior_par = c(0, 1),
  final_ability.estimator = "WL",
  dict = JAJ::JAJ_dict
)

Arguments

num_items	(Integer scalar) Number of items in the test.
take_training	(Logical scalar) Whether to include the training phase. Defaults to TRUE.
with_welcome	(Logical scalar) Whether to include a welcome message. Defaults to TRUE.
with_finish	(logical) Adds a "test finsihed" page at the end.
label	(Character scalar) Label to give the JAJ results in the output file. Defaults to JAJ.
feedback	(Function) Defines the feedback to give the participant at the end of the test. Defaults JAJ::JAJ_feedback_with_score.
next_item.criterion	(Character scalar) Criterion for selecting successive items in the adaptive test. See the criterion argument in nextItem for possible values. Defaults to "bOpt".
next_item.estimator	(Character scalar) Ability estimation method used for selecting successive items in the adaptive test. See the method argument in thetaEst for possible values. "BM", Bayes modal, corresponds to the setting used in the original JAJ paper. "WL", weighted likelihood, corresponds to the default setting used in versions <= 0.2.0 of this package.
next_item.prior_dist	(Character scalar) The type of prior distribution to use when calculating ability estimates for item selection. Ignored if next_item.estimator is not a Bayesian method. Defaults to "norm" for a normal distribution. See the priorDist argument in thetaEst for possible values.
next_item.prior_par	(Numeric vector, length 2) Parameters for the prior distribution; see the priorPar argument in thetaEst for details. Ignored if next_item.estimator is not a Bayesian method. The dfeault is c(0, 1).
final_ability.estimator	Estimation method used for the final ability estimate. See the method argument in thetaEst for possible values. The default is "WL", weighted likelihood. If a Bayesian method is chosen, its prior distribution will be defined by the next_item.prior_dist and next_item.prior_par arguments.
dict	The psychTestR dictionary used for internationalisation. Defaults to JAJ_dict

klausfrieler/JAJ documentation built on May 9, 2023, 8:59 a.m.