Optimal Test Design Approach to Fixed and Adaptive Test
Construction
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Documentation for package ‘TestDesign’ version 1.6.1
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 |
| 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 --
| 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 using standard errors |
| 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 --
| 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 |
| 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 |
| runAssembly | Run Test Assembly |
-- 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_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 |