A B C D E F G I L M O P R S T U misc
| addTrans | Add transparancy to color |
| app | Launch Shiny app |
| array_info_1pl | Calculate Fisher information at multiple thetas (1PL) |
| array_info_2pl | Calculate Fisher information at multiple thetas (2PL) |
| array_info_3pl | Calculate Fisher information at multiple thetas (3PL) |
| array_info_gpc | Calculate Fisher information at multiple thetas (GPC) |
| array_info_gr | Calculate Fisher information at multiple thetas (GR) |
| array_info_pc | Calculate Fisher information at multiple thetas (PC) |
| array_p_1pl | Calculate probability at multiple thetas (1PL) |
| array_p_2pl | Calculate probability at multiple thetas (2PL) |
| array_p_3pl | Calculate probability at multiple thetas (3PL) |
| array_p_gpc | Calculate probability at multiple thetas (GPC) |
| array_p_gr | Calculate probability at multiple thetas (GR) |
| array_p_pc | Calculate probability at multiple thetas (PC) |
| buildConstraints | Build constraints |
| calcDerivative | Calculate first derivative |
| calcDerivative-method | Calculate first derivative |
| calcDerivative2 | Calculate second derivative |
| calcDerivative2-method | Calculate second derivative |
| 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 item location |
| calcLocation-method | Calculate item location |
| calcProb | Calculate item response probabilities |
| calcProb-method | Calculate item response probabilities |
| calcRP | Find matching theta to supplied probability |
| calc_info | Calculate the Fisher information matrix for a single theta value and a set of items, potentially with a mixture of different models |
| calc_info_EB | Calculate the Fisher information using empirical Bayes |
| calc_info_FB | Calculate the Fisher information using full Bayesian |
| 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 |
| calc_likelihood | Calculate a likelihood value of theta |
| calc_likelihood_function | Calculate a likelihood function of theta |
| calc_log_likelihood | Calculate a log-likelihood value of theta |
| calc_log_likelihood_function | Calculate a log-likelihood function of theta |
| 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 |
| config_Shadow-class | createShadowTestConfig |
| config_Static-class | createStaticTestConfig |
| constraint-class | An S4 class to represent a single constraint |
| constraints-class | An S4 class to represent a set of constraints |
| constraints_fatigue | Fatigue dataset |
| constraints_fatigue_raw | Fatigue dataset |
| constraints_reading | Reading dataset |
| constraints_reading_raw | Reading dataset |
| constraints_science | Science dataset |
| constraints_science_raw | Science dataset |
| createShadowTestConfig | createShadowTestConfig |
| createStaticTestConfig | createStaticTestConfig |
| dataset_fatigue | Fatigue dataset |
| dataset_reading | Reading dataset |
| dataset_science | Science dataset |
| EAP | Generate expected a posteriori estimates of theta |
| eap | Generate expected a posteriori estimates of theta |
| EAP-method | Generate expected a posteriori estimates of theta |
| eap-method | Generate expected a posteriori estimates of theta |
| extract-methods | Extract |
| find_segment | Find the segment to which each theta value belongs |
| getSolution | Print solution items |
| getSolution-method | Print solution items |
| info_1pl | Calculate Fisher information at a single theta (1PL) |
| info_2pl | Calculate Fisher information at a single theta (2PL) |
| info_3pl | Calculate Fisher information at a single theta (3PL) |
| info_gpc | Calculate Fisher information at a single theta (GPC). |
| info_gr | Calculate Fisher information at a single theta (GR). |
| info_pc | Calculate Fisher information at a single theta (PC) |
| iparPosteriorSample | Sample item parameter estimates from their posterior distributions |
| itemattrib_fatigue | Fatigue dataset |
| itemattrib_fatigue_raw | Fatigue dataset |
| itemattrib_reading | Reading dataset |
| itemattrib_reading_raw | Reading dataset |
| itemattrib_science | Science dataset |
| itemattrib_science_raw | Science dataset |
| itemcontent_fatigue_raw | Fatigue dataset |
| itempool_fatigue | Fatigue dataset |
| itempool_fatigue_raw | Fatigue dataset |
| itempool_reading | Reading dataset |
| itempool_reading_raw | Reading dataset |
| itempool_science | Science dataset |
| itempool_science_raw | Science dataset |
| item_1PL-class | An S4 class to represent a 1PL item |
| item_2PL-class | An S4 class to represent a 2PL item |
| item_3PL-class | An S4 class to represent a 3PL item |
| item_attrib-class | An S4 class to represent a set of constraints. |
| item_GPC-class | An S4 class to represent a generalized partial credit item |
| item_GR-class | An S4 class to represent a graded response item |
| item_PC-class | An S4 class to represent a partial credit item |
| item_pool-class | An S4 class to represent an item pool |
| item_pool.operators | Item pool and pool cluster operators |
| lnHyperPars | Calculate hyperparameters for log-normal distribution |
| loadConstraints | Load constraints |
| loadItemAttrib | Load item attributes |
| loadItemPool | Load item paramaters |
| loadStAttrib | Load set/stimulus/passage attributes |
| logitHyperPars | Calculate hyperparameters for logit-normal distribution |
| makeItemPoolCluster | Create an item pool cluster object |
| makeTest | Generate a test object |
| makeTest-method | Generate a test object |
| makeTestCluster | Generate a test cluster object |
| makeTestCluster-method | Generate a test cluster object |
| MLE | Generate maximum likelihood estimates of theta |
| mle | Generate maximum likelihood estimates of theta |
| MLE-method | Generate maximum likelihood estimates of theta |
| mle-method | Generate maximum likelihood estimates of theta |
| OAT | Launch Shiny app |
| output_Shadow-class | output_Shadow |
| plotCAT | Draw an audit trail plot |
| plotCAT-method | Draw an audit trail plot |
| plotEligibilityStats | Draw item eligibility statistics plots |
| plotExposure | Draw an item exposure plot |
| plotExposure-method | Draw an item exposure plot |
| plotExposureRateBySegment | Draw exposure rate plots by theta segment |
| plotExposureRateFinal | Draw exposure rate plots by final theta segment |
| plotExposureRateFinalFlag | Draw item information plots for flagged items by segment |
| plotInfo | Draw item information plots |
| plotInfo-method | Draw item information plots |
| plotInfoOverlay | Overlay item information plots |
| plotRMSE | Draw RMSE plots |
| plotShadow | Draw a shadow test chart |
| plotShadow-method | Draw a shadow test chart |
| pool_cluster-class | An S4 class to represent a cluster of item pools |
| p_1pl | Calculate probability at a single theta (1PL) |
| p_2pl | Calculate probability at a single theta (2PL) |
| p_3pl | Calculate probability at a single theta (3PL) |
| p_gpc | Calculate probability at a single theta (GPC) |
| p_gr | Calculate probability at a single theta (GR) |
| p_pc | Calculate probability at a single theta (PC) |
| RE | Calculate Relative Errors |
| resp_fatigue_raw | Fatigue dataset |
| RMSE | Calculate Root Mean Squared Error |
| runAssembly | Run Test Assembly |
| saveOutput | Save or print audit trails |
| Shadow | Run adaptive test assembly. |
| Shadow-method | Run adaptive test assembly. |
| showConstraints | Show constraints |
| simResp | Simulate item responses |
| simResp-method | Simulate item responses |
| Static | Run Static Test Assembly |
| Static-method | Run Static Test Assembly |
| stimattrib_reading | Reading dataset |
| stimattrib_reading_raw | Reading dataset |
| st_attrib-class | An S4 class to represent a set of constraints. |
| subsetItemPool | Create a subset of an item pool object |
| subsetTest | Create a subset of a test object |
| test-class | An S4 class to represent a test |
| test_cluster-class | An S4 class to represent a test cluster |
| theta_EAP | Calculate an EAP estimate of theta for one examinee |
| theta_EAP_matrix | Calculate EAP estimates of theta for a group of examinees |
| theta_EB | Calculate an empirical Bayes estimate of theta for one examinee |
| theta_EB_single | Calculate an empirical Bayes estimate of theta for a single item |
| theta_FB | Calculate a fully Bayesian estimate of theta for an examinee |
| theta_FB_single | Calculate a fully Bayesian estimate of theta for a single item |
| updateConstraints | Update constraints |
| +.item_pool | Item pool and pool cluster operators |
| -.item_pool | Item pool and pool cluster operators |
| ==.item_pool | Item pool and pool cluster operators |
| ==.pool_cluster | Item pool and pool cluster operators |
| [-method | Extract |