Package: TestDesign 1.7.09999
TestDesign: Optimal Test Design Approach to Fixed and Adaptive Test Construction
Uses the optimal test design approach by Birnbaum (1968, ISBN:9781593119348) and van der Linden (2018) <doi:10.1201/9781315117430> 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 <https://www.gurobi.com/downloads/>.
Authors:
TestDesign_1.7.09999.tar.gz
TestDesign_1.7.09999.zip(r-4.5)TestDesign_1.7.09999.zip(r-4.4)TestDesign_1.7.09999.zip(r-4.3)
TestDesign_1.7.09999.tgz(r-4.4-x86_64)TestDesign_1.7.09999.tgz(r-4.4-arm64)TestDesign_1.7.09999.tgz(r-4.3-x86_64)TestDesign_1.7.09999.tgz(r-4.3-arm64)
TestDesign_1.7.09999.tar.gz(r-4.5-noble)TestDesign_1.7.09999.tar.gz(r-4.4-noble)
TestDesign_1.7.09999.tgz(r-4.4-emscripten)TestDesign_1.7.09999.tgz(r-4.3-emscripten)
TestDesign.pdf |TestDesign.html✨
TestDesign/json (API)
NEWS
# Install 'TestDesign' in R: |
install.packages('TestDesign', repos = c('https://choi-phd.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/choi-phd/testdesign/issues
- 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
- 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
- resp_fatigue_data - Fatigue dataset
- stimattrib_reading - Reading dataset
- stimattrib_reading_data - Reading dataset
Last updated 2 months agofrom:9af8b12f95. Checks:OK: 3 NOTE: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 26 2024 |
R-4.5-win-x86_64 | OK | Oct 26 2024 |
R-4.5-linux-x86_64 | OK | Oct 26 2024 |
R-4.4-win-x86_64 | NOTE | Oct 26 2024 |
R-4.4-mac-x86_64 | NOTE | Oct 26 2024 |
R-4.4-mac-aarch64 | NOTE | Oct 26 2024 |
R-4.3-win-x86_64 | NOTE | Oct 26 2024 |
R-4.3-mac-x86_64 | NOTE | Oct 26 2024 |
R-4.3-mac-aarch64 | NOTE | Oct 26 2024 |
Exports:a_to_alphaapparray_dirinfo_m_2plarray_dirinfo_m_3plarray_dirinfo_m_gpcarray_dirinfo_m_grarray_e_1plarray_e_2plarray_e_3plarray_e_gpcarray_e_grarray_e_pcarray_h_1plarray_h_2plarray_h_3plarray_h_gpcarray_h_grarray_h_pcarray_info_1plarray_info_2plarray_info_3plarray_info_gpcarray_info_grarray_info_m_2plarray_info_m_3plarray_info_m_gpcarray_info_m_grarray_info_pcarray_j_1plarray_j_2plarray_j_3plarray_j_gpcarray_j_grarray_j_pcarray_p_1plarray_p_2plarray_p_3plarray_p_gpcarray_p_grarray_p_m_2plarray_p_m_3plarray_p_m_gpcarray_p_m_grarray_p_pcarray_thisdirinfo_m_2plarray_thisdirinfo_m_3plarray_thisdirinfo_m_gpcarray_thisdirinfo_m_gras.data.framebuildConstraintscalc_infocalc_info_matrixcalc_likelihoodcalc_likelihood_functioncalc_log_likelihoodcalc_log_likelihood_functioncalcEscorecalcFishercalcHessiancalcJacobiancalcLocationcalcLogLikelihoodcalcProbcalculateAdaptivityMeasurescombineConstraintscombineItemPoolcreateShadowTestConfigcreateStaticTestConfigdetectBestSolverdirinfo_m_2pldirinfo_m_3pldirinfo_m_gpcdirinfo_m_gre_1ple_2ple_3ple_gpce_gre_m_2ple_m_3ple_m_gpce_m_gre_pceapfind_segmentgetScoreAttributesgetSolutiongetSolutionAttributesh_1plh_2plh_3plh_gpch_grh_m_2plh_m_3plh_m_gpch_m_grh_pcinfo_1plinfo_2plinfo_3plinfo_gpcinfo_grinfo_m_2plinfo_m_3plinfo_m_gpcinfo_m_grinfo_pciparPosteriorSamplej_1plj_2plj_3plj_gpcj_grj_m_2plj_m_3plj_m_gpcj_m_grj_pclnHyperParsloadConstraintsloadItemAttribloadItemPoolloadStAttriblogitHyperParsmakeConstraintsByEachPartitionmakeItemPoolClustermakeSimulationDataCachemakeTestmakeTestClustermlemlefOATp_1plp_2plp_3plp_gpcp_grp_m_2plp_m_3plp_m_gpcp_m_grp_pcplotprintShadowshowsimRespSplitStaticsubsetConstraintssubsetItemPoolsubsetTestsummaryTestDesigntestSolvertheta_EAPtheta_EAP_matrixtheta_EBtheta_EB_singletheta_FBtheta_FB_singlethisdirinfo_m_2plthisdirinfo_m_3plthisdirinfo_m_gpcthisdirinfo_m_grtoggleConstraints
Dependencies:backportscheckmatecodetoolscrayonforeachhighsiteratorslogitnormlpSolveRcppRcppArmadillo
Creating constraints in TestDesign package
Rendered fromconstraints.Rmd
usingknitr::rmarkdown
on Oct 26 2024.Last update: 2024-01-15
Started: 2019-07-15
Installing Rsymphony solver package on Mac
Rendered fromrsymphony.Rmd
usingknitr::rmarkdown
on Oct 26 2024.Last update: 2022-12-14
Started: 2019-07-19
Using Split() for creating parallel tests/pools
Rendered fromsplit.Rmd
usingknitr::rmarkdown
on Oct 26 2024.Last update: 2022-03-02
Started: 2022-02-24
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Calculate alpha angles from a-parameters | a_to_alpha |
Open TestDesign app | app OAT |
Build constraints (shortcut to other loading functions) | buildConstraints |
(C++) For multiple items, calculate Fisher information | calc_info calc_info_matrix |
Calculate the Fisher information using empirical Bayes | calc_info_EB |
Calculate the Fisher information using full Bayesian | calc_info_FB |
(C++) For multiple items, calculate likelihoods | calc_likelihood calc_likelihood_function calc_log_likelihood calc_log_likelihood_function |
Calculate the mutual information using full Bayesian | calc_MI_FB |
Calculate a posterior value of theta | calc_posterior |
Calculate a posterior distribution of theta | calc_posterior_function |
Calculate a posterior value of theta for a single item | calc_posterior_single |
Calculate expected scores | calcEscore calcEscore,item_1PL,matrix-method calcEscore,item_1PL,numeric-method calcEscore,item_2PL,matrix-method calcEscore,item_2PL,numeric-method calcEscore,item_3PL,matrix-method calcEscore,item_3PL,numeric-method calcEscore,item_GPC,matrix-method calcEscore,item_GPC,numeric-method calcEscore,item_GR,matrix-method calcEscore,item_GR,numeric-method calcEscore,item_PC,matrix-method calcEscore,item_PC,numeric-method calcEscore,item_pool,matrix-method calcEscore,item_pool,numeric-method calcEscore,item_pool_cluster,numeric-method |
Calculate Fisher information | calcFisher calcFisher,item_1PL,matrix-method calcFisher,item_1PL,numeric-method calcFisher,item_2PL,matrix-method calcFisher,item_2PL,numeric-method calcFisher,item_3PL,matrix-method calcFisher,item_3PL,numeric-method calcFisher,item_GPC,matrix-method calcFisher,item_GPC,numeric-method calcFisher,item_GR,matrix-method calcFisher,item_GR,numeric-method calcFisher,item_PC,matrix-method calcFisher,item_PC,numeric-method calcFisher,item_pool,matrix-method calcFisher,item_pool,numeric-method calcFisher,item_pool_cluster,numeric-method |
Calculate second derivative of log-likelihood | calcHessian calcHessian,item_1PL,matrix,numeric-method calcHessian,item_1PL,matrix-method calcHessian,item_1PL,numeric,numeric-method calcHessian,item_1PL,numeric-method calcHessian,item_2PL,matrix,numeric-method calcHessian,item_2PL,matrix-method calcHessian,item_2PL,numeric,numeric-method calcHessian,item_2PL,numeric-method calcHessian,item_3PL,matrix,numeric-method calcHessian,item_3PL,matrix-method calcHessian,item_3PL,numeric,numeric-method calcHessian,item_3PL,numeric-method calcHessian,item_GPC,matrix,numeric-method calcHessian,item_GPC,matrix-method calcHessian,item_GPC,numeric,numeric-method calcHessian,item_GPC,numeric-method calcHessian,item_GR,matrix,numeric-method calcHessian,item_GR,matrix-method calcHessian,item_GR,numeric,numeric-method calcHessian,item_GR,numeric-method calcHessian,item_PC,matrix,numeric-method calcHessian,item_PC,matrix-method calcHessian,item_PC,numeric,numeric-method calcHessian,item_PC,numeric-method calcHessian,item_pool,numeric,numeric-method calcHessian,item_pool,numeric-method calcHessian,item_pool_cluster,numeric,list-method calcHessian,item_pool_cluster,numeric-method |
Calculate first derivative of log-likelihood | calcJacobian calcJacobian,item_1PL,matrix,numeric-method calcJacobian,item_1PL,matrix-method calcJacobian,item_1PL,numeric,numeric-method calcJacobian,item_1PL,numeric-method calcJacobian,item_2PL,matrix,numeric-method calcJacobian,item_2PL,matrix-method calcJacobian,item_2PL,numeric,numeric-method calcJacobian,item_2PL,numeric-method calcJacobian,item_3PL,matrix,numeric-method calcJacobian,item_3PL,matrix-method calcJacobian,item_3PL,numeric,numeric-method calcJacobian,item_3PL,numeric-method calcJacobian,item_GPC,matrix,numeric-method calcJacobian,item_GPC,matrix-method calcJacobian,item_GPC,numeric,numeric-method calcJacobian,item_GPC,numeric-method calcJacobian,item_GR,matrix,numeric-method calcJacobian,item_GR,matrix-method calcJacobian,item_GR,numeric,numeric-method calcJacobian,item_GR,numeric-method calcJacobian,item_PC,matrix,numeric-method calcJacobian,item_PC,matrix-method calcJacobian,item_PC,numeric,numeric-method calcJacobian,item_PC,numeric-method calcJacobian,item_pool,numeric,numeric-method calcJacobian,item_pool,numeric-method calcJacobian,item_pool_cluster,numeric,list-method calcJacobian,item_pool_cluster,numeric-method |
Calculate central location (overall difficulty) | calcLocation calcLocation,item_1PL-method calcLocation,item_2PL-method calcLocation,item_3PL-method calcLocation,item_GPC-method calcLocation,item_GR-method calcLocation,item_PC-method calcLocation,item_pool-method calcLocation-methods |
Calculate log-likelihood | calcLogLikelihood calcLogLikelihood,item_pool,matrix,matrix-method calcLogLikelihood,item_pool,matrix,numeric-method calcLogLikelihood,item_pool,numeric,matrix-method calcLogLikelihood,item_pool,numeric,numeric-method |
Calculate item response probabilities | calcProb calcProb,item_1PL,matrix-method calcProb,item_1PL,numeric-method calcProb,item_2PL,matrix-method calcProb,item_2PL,numeric-method calcProb,item_3PL,matrix-method calcProb,item_3PL,numeric-method calcProb,item_GPC,matrix-method calcProb,item_GPC,numeric-method calcProb,item_GR,matrix-method calcProb,item_GR,numeric-method calcProb,item_PC,matrix-method calcProb,item_PC,numeric-method calcProb,item_pool,matrix-method calcProb,item_pool,numeric-method calcProb,item_pool_cluster,numeric-method calcProb-methods |
Calculate Adaptivity Measures | calculateAdaptivityMeasures |
Check the consistency of constraints and item usage | checkConstraints |
Create a config_Shadow object | config_Shadow-class createShadowTestConfig |
Create a config_Static object | config_Static-class createStaticTestConfig |
Class 'constraint': a single constraint | constraint-class |
Class 'constraints': a set of constraints | constraints-class |
Basic operators for constraints objects | c,constraints-method combineConstraints constraints-operators subsetConstraints [,constraints,numeric,ANY,ANY-method [,constraints,numeric-method |
Bayes dataset | constraints_bayes constraints_bayes_data dataset_bayes itemattrib_bayes itemattrib_bayes_data itempool_bayes itempool_bayes_data itempool_se_bayes_data |
Fatigue dataset | constraints_fatigue constraints_fatigue_data dataset_fatigue itemattrib_fatigue itemattrib_fatigue_data itempool_fatigue itempool_fatigue_data itemtext_fatigue_data resp_fatigue_data |
Reading dataset | constraints_reading constraints_reading_data dataset_reading itemattrib_reading itemattrib_reading_data itempool_reading itempool_reading_data stimattrib_reading stimattrib_reading_data |
Science dataset | constraints_science constraints_science_data dataset_science itemattrib_science itemattrib_science_data itempool_science itempool_science_data |
Detect best solver | detectBestSolver |
(C++) Calculate expected scores | array_e_1pl array_e_2pl array_e_3pl array_e_gpc array_e_gr array_e_pc e_1pl e_2pl e_3pl e_gpc e_gr e_item e_m_2pl e_m_3pl e_m_gpc e_m_gr e_pc |
Compute expected a posteriori estimates of theta | EAP eap eap,item_pool-method EAP,test-method EAP,test_cluster-method |
(C++) Classify theta values into segments using cutpoints | find_segment |
Retrieve constraints-related scores from solution | getScoreAttributes |
Print solution items | getSolution getSolution,list-method getSolution,output_Static-method |
Retrieve constraints-related attributes from solution | getSolutionAttributes |
(C++) Calculate second derivative of log-likelihood | array_h_1pl array_h_2pl array_h_3pl array_h_gpc array_h_gr array_h_pc h_1pl h_2pl h_3pl h_gpc h_gr h_item h_m_2pl h_m_3pl h_m_gpc h_m_gr h_pc |
(C++) Calculate Fisher information | array_dirinfo_m_2pl array_dirinfo_m_3pl array_dirinfo_m_gpc array_dirinfo_m_gr array_info_1pl array_info_2pl array_info_3pl array_info_gpc array_info_gr array_info_m_2pl array_info_m_3pl array_info_m_gpc array_info_m_gr array_info_pc array_thisdirinfo_m_2pl array_thisdirinfo_m_3pl array_thisdirinfo_m_gpc array_thisdirinfo_m_gr dirinfo_m_2pl dirinfo_m_3pl dirinfo_m_gpc dirinfo_m_gr info_1pl info_2pl info_3pl info_gpc info_gr info_item info_m_2pl info_m_3pl info_m_gpc info_m_gr info_pc thisdirinfo_m_2pl thisdirinfo_m_3pl thisdirinfo_m_gpc thisdirinfo_m_gr |
Generate item parameter samples for Bayesian purposes | iparPosteriorSample |
Load item attributes | item_attrib-class loadItemAttrib |
Basic functions for item attribute objects | as.data.frame,item_attrib-method colnames,item_attrib-method dim,item_attrib-method item_attrib-operators names,item_attrib-method rownames,item_attrib-method [,item_attrib,numeric,ANY,ANY-method [,item_attrib,numeric-method |
Class 'item_pool_cluster': an item pool | item_pool_cluster-class |
Class 'item_pool': an item pool | item_pool-class |
Basic operators for item pool objects | +.item_pool -.item_pool ==.item_pool c,item_pool-method combineItemPool item_pool-operators subsetItemPool [,item_pool,numeric,ANY,ANY-method [,item_pool,numeric-method |
Item classes | item item-classes item_1PL-class item_2PL-class item_3PL-class item_GPC-class item_GR-class item_PC-class |
(C++) Calculate first derivative of log-likelihood | array_j_1pl array_j_2pl array_j_3pl array_j_gpc array_j_gr array_j_pc j_1pl j_2pl j_3pl j_gpc j_gr j_item j_m_2pl j_m_3pl j_m_gpc j_m_gr j_pc |
Convert mean and standard deviation into log-normal distribution parameters | lnHyperPars |
Load constraints | loadConstraints |
Load item pool | loadItemPool |
Convert mean and standard deviation into logit-normal distribution parameters | logitHyperPars |
make constraints objects from Split() solution indices | makeConstraintsByEachPartition |
Create an item pool cluster object | ==.item_pool_cluster makeItemPoolCluster makeItemPoolCluster,item_pool-method |
Create a simulation data cache object | makeSimulationDataCache makeSimulationDataCache,item_pool-method |
Create a test object | makeTest makeTest,item_pool-method |
Create a test cluster object | makeTestCluster makeTestCluster,item_pool_cluster,numeric,list-method makeTestCluster,item_pool_cluster,numeric,numeric-method |
Compute maximum likelihood estimates of theta | MLE mle mle,item_pool-method MLE,test-method MLE,test_cluster-method |
Compute maximum likelihood estimates of theta using fence items | mlef mlef,item_pool-method |
Class 'output_Shadow_all': a set of adaptive assembly solutions | output_Shadow_all-class |
Class 'output_Shadow': adaptive assembly solution for one simulee | output_Shadow-class |
Class 'output_Split': partitioning solution | output_Split-class |
Class 'output_Static': fixed-form assembly solution | output_Static-class |
(C++) Calculate item response probability | array_p_1pl array_p_2pl array_p_3pl array_p_gpc array_p_gr array_p_m_2pl array_p_m_3pl array_p_m_gpc array_p_m_gr array_p_pc p_1pl p_2pl p_3pl p_gpc p_gr p_item p_m_2pl p_m_3pl p_m_gpc p_m_gr p_pc |
Extension of plot() for objects in TestDesign package | plot plot,constraints-method plot,item_pool-method plot,output_Shadow-method plot,output_Shadow_all-method plot,output_Split-method plot,output_Static-method |
Extension of print() for objects in TestDesign package | print print,config_Shadow-method print,config_Static-method print,constraints-method print,exposure_rate_plot-method print,item_1PL-method print,item_2PL-method print,item_3PL-method print,item_attrib-method print,item_GPC-method print,item_GR-method print,item_PC-method print,item_pool-method print,output_Shadow-method print,output_Shadow_all-method print,output_Static-method print,st_attrib-method print,summary_constraints-method print,summary_item_attrib-method print,summary_item_pool-method print,summary_output_Shadow_all-method print,summary_output_Static-method print,summary_st_attrib-method |
Calculate Relative Errors | RE |
Calculate Root Mean Squared Error | RMSE |
Run adaptive test assembly | Shadow Shadow,config_Shadow-method |
Extension of show() for objects in TestDesign package | show show,config_Shadow-method show,config_Static-method show,constraints-method show,exposure_rate_plot-method show,item_1PL-method show,item_2PL-method show,item_3PL-method show,item_attrib-method show,item_GPC-method show,item_GR-method show,item_PC-method show,item_pool-method show,item_pool_cluster-method show,output_Shadow-method show,output_Shadow_all-method show,output_Static-method show,pool_cluster-method show,st_attrib-method show,summary_constraints-method show,summary_item_attrib-method show,summary_item_pool-method show,summary_output_Shadow_all-method show,summary_output_Static-method show,summary_st_attrib-method |
Simulate item response data | simResp simResp,item_1PL,matrix-method simResp,item_1PL,numeric-method simResp,item_2PL,matrix-method simResp,item_2PL,numeric-method simResp,item_3PL,matrix-method simResp,item_3PL,numeric-method simResp,item_GPC,matrix-method simResp,item_GPC,numeric-method simResp,item_GR,matrix-method simResp,item_GR,numeric-method simResp,item_PC,matrix-method simResp,item_PC,numeric-method simResp,item_pool,matrix-method simResp,item_pool,numeric-method simResp,item_pool_cluster,list-method simResp,item_pool_cluster,numeric-method |
Class 'simulation_data_cache': data cache for Shadow() | simulation_data_cache-class |
Split an item pool into partitions | Split Split,config_Static-method |
Load set/stimulus/passage attributes | loadStAttrib st_attrib-class |
Basic functions for stimulus attribute objects | as.data.frame,st_attrib-method colnames,st_attrib-method dim,st_attrib-method names,st_attrib-method rownames,st_attrib-method st_attrib-operators [,st_attrib,numeric,ANY,ANY-method [,st_attrib,numeric-method |
Run fixed-form test assembly | Static Static,config_Static-method |
Extension of summary() for objects in TestDesign package | summary summary,constraints-method summary,item_attrib-method summary,item_pool-method summary,output_Shadow_all-method summary,output_Static-method summary,st_attrib-method |
Summary classes | summary-classes summary_constraints-class summary_item_attrib-class summary_item_pool-class summary_output_Shadow-class summary_output_Shadow_all-class summary_output_Static-class summary_st_attrib-class |
Class 'test_cluster': data cache for simulations | test_cluster-class |
Basic operators for test objects | subsetTest test_operators [,test,ANY-method [,test,numeric,ANY,ANY-method |
Class 'test': data cache for simulations | test-class |
Open TestDesign app | TestDesign |
Test solver | testSolver |
(C++) Calculate a theta estimate using EAP (expected a posteriori) method | theta_EAP theta_EAP_matrix |
(C++) Calculate a theta estimate using EB (Empirical Bayes) method | theta_EB theta_EB_single |
(C++) Calculate a theta estimate using FB (Full Bayes) method | theta_FB theta_FB_single |
Toggle constraints | toggleConstraints |