MIQ: MIQ

In fmhoeger/MIQ: My IQ Test (MIQ)

Description

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

Usage

MIQ(
  label = "MIQ",
  num_items = 5,
  with_welcome = TRUE,
  take_training = FALSE,
  feedback_page = NULL,
  with_finish = FALSE,
  next_item.criterion = "MFI",
  next_item.estimator = "BM",
  next_item.prior_dist = "norm",
  next_item.prior_par = c(0, 1),
  final_ability.estimator = "WL",
  constrain_answers = FALSE,
  eligible_first_items = c(3),
  dict = MIQ::MIQ_dict
)

Arguments

label	(Character scalar) Label to give the MIQ results in the output file.
num_items	(Integer scalar) Number of items in the test.
with_welcome	(Logical scalar) Whether to display a welcome page. Defaults to TRUE
take_training	(Logical scalar) Whether to include the training phase. Defaults to FALSE.
feedback_page	(Function) Defines a feedback page function for displaying the results to the participant at the end of the test. Defaults to NULL. Possible feedback page functions include "feedback_with_score()", and "feedback_with_graph()".
with_finish	(Logical scalar) Whether to display a finish page. Defaults to FALSE
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 "MFI".
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 MPT 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 default 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.
constrain_answers	(Logical scalar) If TRUE, then item selection will be constrained so that the correct answers are distributed as evenly as possible over the course of the test. We recommend leaving this option disabled.
eligible_first_items	(Character scalar) (NULL or integerish vector) If not NULL, lists the eligible items for the first item in the test, where each item is identified by its 1-indexed row number in item_bank (see adapt_test). For example, c(2, 3, 4) means that the first item will be drawn from rows 2, 3, 4 of the item bank). Default is c(3) (the third item).
dict	(i18n_dict) The psychTestR dictionary used for internationalisation.

fmhoeger/MIQ documentation built on Oct. 7, 2020, 6:56 a.m.