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TestDesign (version 1.0.2)

Optimal Test Design Approach to Fixed and Adaptive Test Construction

Description

Use the optimal test design approach by Birnbaum (1968, ISBN:9781593119348) and van der Linden (2018) in constructing fixed and adaptive tests. Supports the following mixed-integer programming (MIP) solver packages: 'lpsymphony', 'Rsymphony', 'gurobi', 'lpSolve', and 'Rglpk'. The 'gurobi' package is not available from CRAN; see . See vignette for installing 'Rsymphony' package on Mac systems.

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Install

install.packages('TestDesign')

Monthly Downloads

493

Version

1.0.2

License

GPL (>= 2)

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Repository

https://github.com/choi-phd/TestDesign

Maintainer

Seung W. Choi

Last Published

February 6th, 2020

Functions in TestDesign (1.0.2)

Calculate Fisher information at multiple thetas (GR)

Calculate Fisher information at multiple thetas (PC)

Calculate probability at multiple thetas (2PL)

Calculate probability at multiple thetas (1PL)

Calculate item location

Calculate first derivative of log-likelihood

Calculate second derivative of log-likelihood

Calculate Fisher information

buildConstraints

Build constraints

Calculate first derivative

Calculate item response probabilities

calc_info_matrix

Calculate the Fisher information matrix for a vector of theta values and a set of items, potentially with a mixture of different models

Calculate probability at multiple thetas (PC)

Calculate expected scores

Calculate probability at multiple thetas (GR)

calc_posterior_function

Calculate a posterior distribution of theta

calc_log_likelihood_function

Calculate a log-likelihood function of theta

calcDerivative2

Calculate second derivative

Find matching theta to supplied probability

Calculate probability at multiple thetas (3PL)

Calculate Fisher information at multiple thetas (2PL)

Calculate probability at multiple thetas (GPC)

calc_likelihood

Calculate a likelihood value of theta

calc_posterior_single

Calculate a posterior value of theta for a single item

Calculate a posterior value of theta

Calculate Fisher information at a single theta (1PL)

An S4 class to represent a generalized partial credit item

dataset_fatigue

Fatigue dataset

makeItemPoolCluster

Create an item pool cluster object

An S4 class to represent a 3PL item

plotEligibilityStats

Draw item eligibility statistics plots

config_Static-class

createStaticTestConfig

Calculate hyperparameters for logit-normal distribution

Print solution items

Generate expected a posteriori estimates of theta

Generate expected a posteriori estimates of theta

Calculate Fisher information at a single theta (GR).

An S4 class to represent a 1PL item

Generate a test object

Calculate Fisher information at a single theta (GPC).

An S4 class to represent a 2PL item

Calculate the Fisher information matrix for a single theta value and a set of items, potentially with a mixture of different models

calc_likelihood_function

Calculate a likelihood function of theta

calc_log_likelihood

Calculate a log-likelihood value of theta

Calculate the mutual information using full Bayesian

checkConstraints

Check the consistency of constraints and item usage

Draw an item exposure plot

Calculate Fisher information at a single theta (2PL)

Calculate Fisher information at a single theta (3PL)

config_Shadow-class

createShadowTestConfig

Calculate the Fisher information using empirical Bayes

constraints-class

An S4 class to represent a set of constraints

constraint-class

An S4 class to represent a single constraint

Draw RMSE plots

theta_EAP_matrix

Calculate EAP estimates of theta for a group of examinees

plotInfoOverlay

Overlay item information plots

Calculate an empirical Bayes estimate of theta for one examinee

extract-methods

output_Shadow-class

makeTestCluster

Generate a test cluster object

Calculate probability at a single theta (1PL)

plotExposureRateBySegment

Draw exposure rate plots by theta segment

Calculate the Fisher information using full Bayesian

plotExposureRateFinal

Draw exposure rate plots by final theta segment

item_attrib-class

An S4 class to represent a set of constraints.

item_pool-class

An S4 class to represent an item pool

Find the segment to which each theta value belongs

Create a subset of a test object

An S4 class to represent a test

Calculate probability at a single theta (GPC)

Load item attributes

loadConstraints

Load constraints

dataset_reading

Reading dataset

Calculate probability at a single theta (GR)

item_pool.operators

Item pool and pool cluster operators

Calculate probability at a single theta (2PL)

dataset_science

Science dataset

Load item paramaters

iparPosteriorSample

Sample item parameter estimates from their posterior distributions

Calculate hyperparameters for log-normal distribution

Calculate Fisher information at a single theta (PC)

Calculate probability at a single theta (3PL)

Load set/stimulus/passage attributes

plotExposureRateFinalFlag

Draw item information plots for flagged items by segment

Draw item information plots

Run Test Assembly

Calculate an EAP estimate of theta for one examinee

test_cluster-class

An S4 class to represent a test cluster

Calculate probability at a single theta (PC)

Generate maximum likelihood estimates of theta

An S4 class to represent a partial credit item

An S4 class to represent a graded response item

Generate maximum likelihood estimates of theta

Save or print audit trails

Draw an audit trail plot

Draw a shadow test chart

pool_cluster-class

An S4 class to represent a cluster of item pools

st_attrib-class

An S4 class to represent a set of constraints.

Create a subset of an item pool object

updateConstraints

Update constraints

theta_FB_single

Calculate a fully Bayesian estimate of theta for a single item

showConstraints

Show constraints

Simulate item responses

theta_EB_single

Calculate an empirical Bayes estimate of theta for a single item

Calculate a fully Bayesian estimate of theta for an examinee

Launch Shiny app

Add transparancy to color

Run Static Test Assembly

Run adaptive test assembly.

Calculate Root Mean Squared Error

Calculate Fisher information at multiple thetas (1PL)

Calculate Relative Errors

Calculate Fisher information at multiple thetas (3PL)

Calculate Fisher information at multiple thetas (GPC)