Learn R Programming

TestDesign (version 1.7.0)

Optimal Test Design Approach to Fixed and Adaptive Test Construction

Description

Uses the optimal test design approach by Birnbaum (1968, ISBN:9781593119348) and van der Linden (2018) to construct fixed, adaptive, and parallel tests. Supports the following mixed-integer programming (MIP) solver packages: 'Rsymphony', 'highs', 'gurobi', 'lpSolve', and 'Rglpk'. The 'gurobi' package is not available from CRAN; see .

Copy Link

Version

Install

install.packages('TestDesign')

Monthly Downloads

493

Version

1.7.0

License

GPL (>= 2)

Maintainer

Seung W. Choi

Last Published

August 22nd, 2024

Functions in TestDesign (1.7.0)

addSolutionToConstraintData

(Internal) Count number of items in a solution that match a constraint

applyEligibilityConstraintsToXdata

(Internal) Augment constraint matrix-data with eligibility constraints

applyEligibilityConstraintsToInfo

(Internal) Modify item information using eligibility constraints

(Internal) Apply fading to exposure record

applyShrinkageCorrection

(Internal) Apply shrinkage correction to theta estimate

buildConstraints

Build constraints (shortcut to other loading functions)

Calculate Fisher information

Calculate expected scores

Calculate second derivative of log-likelihood

Calculate first derivative of log-likelihood

calcLocation-methods

Calculate central location (overall difficulty)

(Internal) Thin a MCMC chain

assembleShadowTest

(Internal) Assemble a shadowtest

calculateAdaptivityMeasures

Calculate Adaptivity Measures

calc_posterior_single

Calculate a posterior value of theta for a single item

calcLogLikelihood

Calculate log-likelihood

calcProb-methods

Calculate item response probabilities

calc_posterior_function

Calculate a posterior distribution of theta

assemblyInFinalThetaSegmentWasFeasibleAtLeastOnceInInterimThetaSegments

(Internal) Determine if shadowtest assembly was feasible for exposure control purposes

applyOverlapConstraintsToInfo

(Internal) Modify item information using overlap constraints

Calculate the mutual information using full Bayesian

Calculate the Fisher information using full Bayesian

constraints-operators

Basic operators for constraints objects

(C++) For multiple items, calculate Fisher information

Calculate the Fisher information using empirical Bayes

computeEAPFromPosterior

(Internal) Convert posterior densities into an EAP estimate

(Internal) Combine two constraint matrix-data

constraints-class

Class 'constraints': a set of constraints

checkConstraints

Check the consistency of constraints and item usage

constraint-class

Class 'constraint': a single constraint

combineItemPoolData

(Internal) Combine item pool data

config_Static-class

Create a config_Static object

computeInfoAtCurrentTheta

(Internal) Compute item information at current theta estimate

calc_likelihood

(C++) For multiple items, calculate likelihoods

Calculate a posterior value of theta

determineCurrentThetaSegment

(Internal) Determine the current theta segment

detectBestSolver

Detect best solver

config_Shadow-class

Create a config_Shadow object

dataset_science

Science dataset

(Internal) Obtain item/set level eligibility flags

generateSampleFromPriorPar

(Internal) Generate random theta samples from prior distribution

generateItemParameterSample

(Internal) Generate item parameter samples for Bayesian purposes

generateDensityFromPriorPar

(Internal) Convert prior parameters to distribution densities

combineConstraintsData

(Internal) Combine constraints data

getIndexOfExcludedEntry

(Internal) Convert item IDs to item indices for exclusion

getInfoFixedTheta

(Internal) Precalculate item information for fixed-theta item selection methods

doExposureControl

(Internal) Perform exposure control

estimateInterimTheta

(Internal) Estimate interim theta

estimateFinalTheta

(Internal) Estimate final theta

(Internal) Package startup functions

clipEligibilityRates

(Internal) Clip eligibility rates into 0-1 bounds

getInfoOfExcludedEntry

(Internal) Apply information penalty on items to be excluded

Compute expected a posteriori estimates of theta

getSolutionAttributes

Retrieve constraints-related attributes from solution

(C++) Calculate expected scores

getDecisionVariablesOfItemForMultipool

(Internal) Make decision variables for selecting an item

dataset_fatigue

Fatigue dataset

getXdataOfAdministered

(Internal) Obtain constraint matrix-data of administered items/sets

getEligibilityFlagInSegment

(Internal) Parse eligibility flags for a specific theta segment

(Internal) Convert a theta distribution to segment-wise classification probabilities

(Internal) Calculate theta segment of a given examinee

dataset_reading

Reading dataset

initializeDiagnosticExposureRecord

(Internal) Initialize diagnostic exposure record

getDecisionVariablesOfPoolForMultipool

(Internal) Make decision variables for selecting a pool

(C++) Calculate Fisher information

getXdataOfExcludedEntry

(Internal) Translate item exclusion instructions into a constraint matrix-data

(C++) Calculate second derivative of log-likelihood

Convert mean and standard deviation into log-normal distribution parameters

iparPosteriorSample

Generate item parameter samples for Bayesian purposes

(C++) Calculate first derivative of log-likelihood

isCustomFirstSegmentAvailable

(Internal) Check if customized first segments are available

item_pool-class

Class 'item_pool': an item pool

item_pool-operators

Basic operators for item pool objects

initializeCompletedGroupingsRecord

(Internal) Initialize groupings record

initializeUsageMatrix

(Internal) Initialize item usage matrix

initializeSegmentRecord

(Internal) Initialize segment record

isSolutionOptimal

(Internal) Check whether solution is optimal

item_attrib-operators

Basic functions for item attribute objects

makeSimulationDataCache

Create a simulation data cache object

Print solution items

validateDifficulty

(Internal) Validate item objects

(C++) Classify theta values into segments using cutpoints

st_attrib-class

Load set/stimulus/passage attributes

makeSetStructureConstraints

(Internal) Make set-based strucutre constraints

initializeExposureRecord

(Internal) Initialize exposure record

makeDiagnosticExposureRecord

(Internal) Collect diagnostic exposure record

(Internal) Bind matrices diagonally

getBayesianConstants

(Internal) Parse Bayesian-related constants

getScoreAttributes

Retrieve constraints-related scores from solution

loadConstraints

Load constraints

(Internal) Increment exposure record variable: phi

getSegmentsToApply

(Internal) Make a vector for segment-dimensioned matrix update

getLBUBInConstraintData

(Internal) Parse item/stimulus lower/upper bounds from constraints data

flagAdministeredAsEligible

(Internal) Update eligibility flags to mark administered items as eligible

(Internal) Parse constants for adaptive test assembly simulation

(Internal) Increment exposure record variable: n

(Internal) Increment exposure record variable: rho

output_Split-class

Class 'output_Split': partitioning solution

Compute maximum likelihood estimates of theta using fence items

parseConstraintData

(Internal) Parse a constraint data into an object

(Internal) Increment exposure record variable: alpha

item_attrib-class

Load item attributes

output_Shadow_all-class

Class 'output_Shadow_all': a set of adaptive assembly solutions

(C++) Calculate item response probability

output_Static-class

Class 'output_Static': fixed-form assembly solution

Simulate item response data

simulation_data_cache-class

Class 'simulation_data_cache': data cache for Shadow()

Extension of print() for objects in TestDesign package

Extension of show() for objects in TestDesign package

(Internal) Plot test information of a single shadow test

shouldShadowTestBeRefreshed

(Internal) Determine whether shadowtest should be refreshed

st_attrib-operators

Basic functions for stimulus attribute objects

parsePriorParameters

(Internal) Parse prior parameters from viable sources

splitSolutionToBins

(Internal) Convert a partitioning problem solution to indices

plotShadowAudit

(Internal) Plot audit trail of a single examinee

plotExposurePanel

(Internal) Draw an exposure rate plot

(C++) Calculate a theta estimate using EAP (expected a posteriori) method

(C++) Calculate a theta estimate using EB (Empirical Bayes) method

validateFullColumn

(Internal) Validate constraint for completeness of its required attribute column

makeItemPoolCluster

Create an item pool cluster object

Convert mean and standard deviation into logit-normal distribution parameters

item_pool_cluster-class

Class 'item_pool_cluster': an item pool

(Internal) Validate constraint lower/upper bounds

plotShadowChart

(Internal) Plot shadow chart of a single examinee

Class 'test': data cache for simulations

Create a test object

Extension of plot() for objects in TestDesign package

output_Shadow-class

Class 'output_Shadow': adaptive assembly solution for one simulee

summary-classes

Summary classes

parseShadowTestRefreshSchedule

(Internal) Parse shadowtest refresh schedule

selectItemFromShadowTest

(Internal) Select item from a shadowtest

plotShadowExposure

(Internal) Plot exposure rates from a simulation

(Internal) Sanitize item model names for C++ functions

makeConstraintsByEachPartition

make constraints objects from Split() solution indices

test_cluster-class

Class 'test_cluster': data cache for simulations

Basic operators for test objects

updateSegmentRecord

(Internal) Update segment record

updateEligibilityRates

(Internal) Update eligibility rates based on exposure rates

makeTestCluster

Create a test cluster object

(Internal) Validate solver for interactive use

updateDiagnosticExposureRecord

(Internal) Update diagnostic exposure record

updateCompletedGroupingsRecordForStimulus

(Internal) Update groupings record for stimulus

Extension of summary() for objects in TestDesign package

Compute maximum likelihood estimates of theta

(Internal) Return S4 object validation error messages

toggleConstraints

Toggle constraints

(C++) Calculate a theta estimate using FB (Full Bayes) method

sanitizeConstraintsData

(Internal) Sanitize constraints data

(Internal) Run MIP solver

updateUsageMatrix

(Internal) Update item usage matrix

updateThetaPosterior

(Internal) Update posterior densities

Run Test Assembly

validateConstraintData

(Internal) Validate constraint (wrapper for other validators)

validateExpression

(Internal) Validate constraint condition expression

Calculate Root Mean Squared Error

addCountsToConstraintData

(Internal) Count number of pool items that match a constraint

Calculate Relative Errors

Run adaptive test assembly

Split an item pool into partitions

Run fixed-form test assembly

Open TestDesign app

addScoreToConstraintData

(Internal) Sum scores of items in a solution that match a constraint

adjustAlphaToReduceSpike

(Internal) Apply spike-reduction mechanism on exposure rates

Open TestDesign app

Calculate alpha angles from a-parameters

aggregateUsageMatrix

(Internal) Aggregate item usage matrix into exposure rate table

(Internal) Append mean information to shadowtest