# Optimal Test Design Approach to Fixed and Adaptive Test Construction

## Documentation for package ‘TestDesign’ version 1.7.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS

## Help Pages

A B C D E F G H I J L M N O P R S T misc

## -- A --

app | Open TestDesign app
array_dirinfo_m_2pl | (C++) Calculate Fisher information
array_dirinfo_m_3pl | (C++) Calculate Fisher information
array_dirinfo_m_gpc | (C++) Calculate Fisher information
array_dirinfo_m_gr | (C++) Calculate Fisher information
array_e_1pl | (C++) Calculate expected scores
array_e_2pl | (C++) Calculate expected scores
array_e_3pl | (C++) Calculate expected scores
array_e_gpc | (C++) Calculate expected scores
array_e_gr | (C++) Calculate expected scores
array_e_pc | (C++) Calculate expected scores
array_h_1pl | (C++) Calculate second derivative of log-likelihood
array_h_2pl | (C++) Calculate second derivative of log-likelihood
array_h_3pl | (C++) Calculate second derivative of log-likelihood
array_h_gpc | (C++) Calculate second derivative of log-likelihood
array_h_gr | (C++) Calculate second derivative of log-likelihood
array_h_pc | (C++) Calculate second derivative of log-likelihood
array_info_1pl | (C++) Calculate Fisher information
array_info_2pl | (C++) Calculate Fisher information
array_info_3pl | (C++) Calculate Fisher information
array_info_gpc | (C++) Calculate Fisher information
array_info_gr | (C++) Calculate Fisher information
array_info_m_2pl | (C++) Calculate Fisher information
array_info_m_3pl | (C++) Calculate Fisher information
array_info_m_gpc | (C++) Calculate Fisher information
array_info_m_gr | (C++) Calculate Fisher information
array_info_pc | (C++) Calculate Fisher information
array_j_1pl | (C++) Calculate first derivative of log-likelihood
array_j_2pl | (C++) Calculate first derivative of log-likelihood
array_j_3pl | (C++) Calculate first derivative of log-likelihood
array_j_gpc | (C++) Calculate first derivative of log-likelihood
array_j_gr | (C++) Calculate first derivative of log-likelihood
array_j_pc | (C++) Calculate first derivative of log-likelihood
array_p_1pl | (C++) Calculate item response probability
array_p_2pl | (C++) Calculate item response probability
array_p_3pl | (C++) Calculate item response probability
array_p_gpc | (C++) Calculate item response probability
array_p_gr | (C++) Calculate item response probability
array_p_m_2pl | (C++) Calculate item response probability
array_p_m_3pl | (C++) Calculate item response probability
array_p_m_gpc | (C++) Calculate item response probability
array_p_m_gr | (C++) Calculate item response probability
array_p_pc | (C++) Calculate item response probability
array_thisdirinfo_m_2pl | (C++) Calculate Fisher information
array_thisdirinfo_m_3pl | (C++) Calculate Fisher information
array_thisdirinfo_m_gpc | (C++) Calculate Fisher information
array_thisdirinfo_m_gr | (C++) Calculate Fisher information
as.data.frame-method | Basic functions for item attribute objects
as.data.frame-method | Basic functions for stimulus attribute objects
a_to_alpha | Calculate alpha angles from a-parameters

## -- B --

buildConstraints | Build constraints (shortcut to other loading functions)

## -- C --

c-method | Basic operators for constraints objects
c-method | Basic operators for item pool objects
calcEscore | Calculate expected scores
calcEscore-method | Calculate expected scores
calcFisher | Calculate Fisher information
calcFisher-method | Calculate Fisher information
calcHessian | Calculate second derivative of log-likelihood
calcHessian-method | Calculate second derivative of log-likelihood
calcJacobian | Calculate first derivative of log-likelihood
calcJacobian-method | Calculate first derivative of log-likelihood
calcLocation | Calculate central location (overall difficulty)
calcLocation-method | Calculate central location (overall difficulty)
calcLocation-methods | Calculate central location (overall difficulty)
calcLogLikelihood | Calculate log-likelihood
calcLogLikelihood-method | Calculate log-likelihood
calcProb | Calculate item response probabilities
calcProb-method | Calculate item response probabilities
calcProb-methods | Calculate item response probabilities
calculateAdaptivityMeasures | Calculate Adaptivity Measures
calc_info | (C++) For multiple items, calculate Fisher information
calc_info_EB | Calculate the Fisher information using empirical Bayes
calc_info_FB | Calculate the Fisher information using full Bayesian
calc_info_matrix | (C++) For multiple items, calculate Fisher information
calc_likelihood | (C++) For multiple items, calculate likelihoods
calc_likelihood_function | (C++) For multiple items, calculate likelihoods
calc_log_likelihood | (C++) For multiple items, calculate likelihoods
calc_log_likelihood_function | (C++) For multiple items, calculate likelihoods
calc_MI_FB | Calculate the mutual information using full Bayesian
calc_posterior | Calculate a posterior value of theta
calc_posterior_function | Calculate a posterior distribution of theta
calc_posterior_single | Calculate a posterior value of theta for a single item
checkConstraints | Check the consistency of constraints and item usage
colnames-method | Basic functions for item attribute objects
colnames-method | Basic functions for stimulus attribute objects
combineConstraints | Basic operators for constraints objects
combineItemPool | Basic operators for item pool objects
config_Shadow-class | Create a config_Shadow object
config_Static-class | Create a config_Static object
constraint-class | Class 'constraint': a single constraint
constraints-class | Class 'constraints': a set of constraints
constraints-operators | Basic operators for constraints objects
constraints_bayes | Bayes dataset
constraints_bayes_data | Bayes dataset
constraints_fatigue | Fatigue dataset
constraints_fatigue_data | Fatigue dataset
constraints_reading | Reading dataset
constraints_reading_data | Reading dataset
constraints_science | Science dataset
constraints_science_data | Science dataset
createShadowTestConfig | Create a config_Shadow object
createStaticTestConfig | Create a config_Static object

## -- D --

dataset_bayes | Bayes dataset
dataset_fatigue | Fatigue dataset
dataset_reading | Reading dataset
dataset_science | Science dataset
detectBestSolver | Detect best solver
dim-method | Basic functions for item attribute objects
dim-method | Basic functions for stimulus attribute objects
dirinfo_m_2pl | (C++) Calculate Fisher information
dirinfo_m_3pl | (C++) Calculate Fisher information
dirinfo_m_gpc | (C++) Calculate Fisher information
dirinfo_m_gr | (C++) Calculate Fisher information

## -- E --

EAP | Compute expected a posteriori estimates of theta
eap | Compute expected a posteriori estimates of theta
EAP-method | Compute expected a posteriori estimates of theta
eap-method | Compute expected a posteriori estimates of theta
e_1pl | (C++) Calculate expected scores
e_2pl | (C++) Calculate expected scores
e_3pl | (C++) Calculate expected scores
e_gpc | (C++) Calculate expected scores
e_gr | (C++) Calculate expected scores
e_item | (C++) Calculate expected scores
e_m_2pl | (C++) Calculate expected scores
e_m_3pl | (C++) Calculate expected scores
e_m_gpc | (C++) Calculate expected scores
e_m_gr | (C++) Calculate expected scores
e_pc | (C++) Calculate expected scores

## -- F --

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

## -- G --

getScoreAttributes | Retrieve constraints-related scores from solution
getSolution | Print solution items
getSolution-method | Print solution items
getSolutionAttributes | Retrieve constraints-related attributes from solution

## -- H --

h_1pl | (C++) Calculate second derivative of log-likelihood
h_2pl | (C++) Calculate second derivative of log-likelihood
h_3pl | (C++) Calculate second derivative of log-likelihood
h_gpc | (C++) Calculate second derivative of log-likelihood
h_gr | (C++) Calculate second derivative of log-likelihood
h_item | (C++) Calculate second derivative of log-likelihood
h_m_2pl | (C++) Calculate second derivative of log-likelihood
h_m_3pl | (C++) Calculate second derivative of log-likelihood
h_m_gpc | (C++) Calculate second derivative of log-likelihood
h_m_gr | (C++) Calculate second derivative of log-likelihood
h_pc | (C++) Calculate second derivative of log-likelihood

## -- I --

info_1pl | (C++) Calculate Fisher information
info_2pl | (C++) Calculate Fisher information
info_3pl | (C++) Calculate Fisher information
info_gpc | (C++) Calculate Fisher information
info_gr | (C++) Calculate Fisher information
info_item | (C++) Calculate Fisher information
info_m_2pl | (C++) Calculate Fisher information
info_m_3pl | (C++) Calculate Fisher information
info_m_gpc | (C++) Calculate Fisher information
info_m_gr | (C++) Calculate Fisher information
info_pc | (C++) Calculate Fisher information
iparPosteriorSample | Generate item parameter samples for Bayesian purposes
item | Item classes
item-classes | Item classes
itemattrib_bayes | Bayes dataset
itemattrib_bayes_data | Bayes dataset
itemattrib_fatigue | Fatigue dataset
itemattrib_fatigue_data | Fatigue dataset
itemattrib_reading | Reading dataset
itemattrib_reading_data | Reading dataset
itemattrib_science | Science dataset
itemattrib_science_data | Science dataset
itempool_bayes | Bayes dataset
itempool_bayes_data | Bayes dataset
itempool_fatigue | Fatigue dataset
itempool_fatigue_data | Fatigue dataset
itempool_reading | Reading dataset
itempool_reading_data | Reading dataset
itempool_science | Science dataset
itempool_science_data | Science dataset
itempool_se_bayes_data | Bayes dataset
itemtext_fatigue_data | Fatigue dataset
item_1PL-class | Item classes
item_2PL-class | Item classes
item_3PL-class | Item classes
item_attrib-class | Load item attributes
item_attrib-operators | Basic functions for item attribute objects
item_GPC-class | Item classes
item_GR-class | Item classes
item_PC-class | Item classes
item_pool-class | Class 'item_pool': an item pool
item_pool-operators | Basic operators for item pool objects
item_pool_cluster-class | Class 'item_pool_cluster': an item pool

## -- J --

j_1pl | (C++) Calculate first derivative of log-likelihood
j_2pl | (C++) Calculate first derivative of log-likelihood
j_3pl | (C++) Calculate first derivative of log-likelihood
j_gpc | (C++) Calculate first derivative of log-likelihood
j_gr | (C++) Calculate first derivative of log-likelihood
j_item | (C++) Calculate first derivative of log-likelihood
j_m_2pl | (C++) Calculate first derivative of log-likelihood
j_m_3pl | (C++) Calculate first derivative of log-likelihood
j_m_gpc | (C++) Calculate first derivative of log-likelihood
j_m_gr | (C++) Calculate first derivative of log-likelihood
j_pc | (C++) Calculate first derivative of log-likelihood

## -- L --

lnHyperPars | Convert mean and standard deviation into log-normal distribution parameters
loadConstraints | Load constraints
loadItemAttrib | Load item attributes
loadItemPool | Load item pool
loadStAttrib | Load set/stimulus/passage attributes
logitHyperPars | Convert mean and standard deviation into logit-normal distribution parameters

## -- M --

makeConstraintsByEachPartition | make constraints objects from Split() solution indices
makeItemPoolCluster | Create an item pool cluster object
makeItemPoolCluster-method | Create an item pool cluster object
makeSimulationDataCache | Create a simulation data cache object
makeSimulationDataCache-method | Create a simulation data cache object
makeTest | Create a test object
makeTest-method | Create a test object
makeTestCluster | Create a test cluster object
makeTestCluster-method | Create a test cluster object
MLE | Compute maximum likelihood estimates of theta
mle | Compute maximum likelihood estimates of theta
MLE-method | Compute maximum likelihood estimates of theta
mle-method | Compute maximum likelihood estimates of theta
mlef | Compute maximum likelihood estimates of theta using fence items
mlef-method | Compute maximum likelihood estimates of theta using fence items

## -- N --

names-method | Basic functions for item attribute objects
names-method | Basic functions for stimulus attribute objects

## -- O --

OAT | Open TestDesign app
output_Shadow-class | Class 'output_Shadow': adaptive assembly solution for one simulee
output_Shadow_all-class | Class 'output_Shadow_all': a set of adaptive assembly solutions
output_Split-class | Class 'output_Split': partitioning solution
output_Static-class | Class 'output_Static': fixed-form assembly solution

## -- P --

plot | Extension of plot() for objects in TestDesign package
plot-method | Extension of plot() for objects in TestDesign package
print | Extension of print() for objects in TestDesign package
print-method | Extension of print() for objects in TestDesign package
p_1pl | (C++) Calculate item response probability
p_2pl | (C++) Calculate item response probability
p_3pl | (C++) Calculate item response probability
p_gpc | (C++) Calculate item response probability
p_gr | (C++) Calculate item response probability
p_item | (C++) Calculate item response probability
p_m_2pl | (C++) Calculate item response probability
p_m_3pl | (C++) Calculate item response probability
p_m_gpc | (C++) Calculate item response probability
p_m_gr | (C++) Calculate item response probability
p_pc | (C++) Calculate item response probability

## -- R --

RE | Calculate Relative Errors
resp_fatigue_data | Fatigue dataset
RMSE | Calculate Root Mean Squared Error
rownames-method | Basic functions for item attribute objects
rownames-method | Basic functions for stimulus attribute objects

## -- S --

Shadow | Run adaptive test assembly
Shadow-method | Run adaptive test assembly
show | Extension of show() for objects in TestDesign package
show-method | Extension of show() for objects in TestDesign package
simResp | Simulate item response data
simResp-method | Simulate item response data
simulation_data_cache-class | Class 'simulation_data_cache': data cache for Shadow()
Split | Split an item pool into partitions
Split-method | Split an item pool into partitions
Static | Run fixed-form test assembly
Static-method | Run fixed-form test assembly
stimattrib_reading | Reading dataset
stimattrib_reading_data | Reading dataset
st_attrib-class | Load set/stimulus/passage attributes
st_attrib-operators | Basic functions for stimulus attribute objects
subsetConstraints | Basic operators for constraints objects
subsetItemPool | Basic operators for item pool objects
subsetTest | Basic operators for test objects
summary | Extension of summary() for objects in TestDesign package
summary-classes | Summary classes
summary-method | Extension of summary() for objects in TestDesign package
summary_constraints-class | Summary classes
summary_item_attrib-class | Summary classes
summary_item_pool-class | Summary classes
summary_output_Shadow-class | Summary classes
summary_output_Shadow_all-class | Summary classes
summary_output_Static-class | Summary classes
summary_st_attrib-class | Summary classes

## -- T --

test-class | Class 'test': data cache for simulations
TestDesign | Open TestDesign app
testSolver | Test solver
test_cluster-class | Class 'test_cluster': data cache for simulations
test_operators | Basic operators for test objects
theta_EAP | (C++) Calculate a theta estimate using EAP (expected a posteriori) method
theta_EAP_matrix | (C++) Calculate a theta estimate using EAP (expected a posteriori) method
theta_EB | (C++) Calculate a theta estimate using EB (Empirical Bayes) method
theta_EB_single | (C++) Calculate a theta estimate using EB (Empirical Bayes) method
theta_FB | (C++) Calculate a theta estimate using FB (Full Bayes) method
theta_FB_single | (C++) Calculate a theta estimate using FB (Full Bayes) method
thisdirinfo_m_2pl | (C++) Calculate Fisher information
thisdirinfo_m_3pl | (C++) Calculate Fisher information
thisdirinfo_m_gpc | (C++) Calculate Fisher information
thisdirinfo_m_gr | (C++) Calculate Fisher information
toggleConstraints | Toggle constraints

## -- misc --

+.item_pool | Basic operators for item pool objects
-.item_pool | Basic operators for item pool objects
==.item_pool | Basic operators for item pool objects
==.item_pool_cluster | Create an item pool cluster object
[-method | Basic operators for constraints objects
[-method | Basic functions for item attribute objects
[-method | Basic operators for item pool objects
[-method | Basic functions for stimulus attribute objects
[-method | Basic operators for test objects