Calculate probability at multiple thetas (3PL)
Calculate first derivative
Calculate a likelihood value of theta
Calculate expected scores
Build constraints
Calculate second derivative
Calculate the Fisher information matrix for a vector of theta values and a set of items, potentially with a mixture of different models
Calculate probability at multiple thetas (GPC)
Calculate Fisher information at multiple thetas (GPC)
Calculate second derivative of log-likelihood
Calculate Fisher information
Calculate Fisher information at multiple thetas (GR)
Calculate Fisher information at multiple thetas (PC)
Calculate item location
Calculate probability at multiple thetas (PC)
Calculate the Fisher information using full Bayesian
Calculate probability at multiple thetas (GR)
Reading dataset
Calculate first derivative of log-likelihood
Calculate the Fisher information using empirical Bayes
calc_log_likelihood_function
Calculate a log-likelihood function of theta
Print solution items
Science dataset
createStaticTestConfig
Calculate Fisher information at a single theta (1PL)
Generate expected a posteriori estimates of theta
Generate expected a posteriori estimates of theta
Calculate a posterior value of theta
Calculate the mutual information using full Bayesian
Calculate Fisher information at a single theta (GPC).
Calculate a likelihood function of theta
Calculate the Fisher information matrix for a single theta value and a set of items, potentially with a mixture of different models
Calculate probability at multiple thetas (1PL)
Fatigue dataset
Calculate probability at multiple thetas (2PL)
Calculate item response probabilities
Find matching theta to supplied probability
Calculate Fisher information at a single theta (GR).
Calculate a posterior distribution of theta
Calculate Fisher information at a single theta (2PL)
Item pool and pool cluster operators
An S4 class to represent a set of constraints
An S4 class to represent a set of constraints.
Extract
An S4 class to represent an item pool
Find the segment to which each theta value belongs
Calculate a posterior value of theta for a single item
createShadowTestConfig
An S4 class to represent a 3PL item
An S4 class to represent a generalized partial credit item
Calculate Fisher information at a single theta (3PL)
Calculate hyperparameters for log-normal distribution
Calculate a log-likelihood value of theta
An S4 class to represent a graded response item
Calculate Fisher information at a single theta (PC)
Check the consistency of constraints and item usage
Sample item parameter estimates from their posterior distributions
An S4 class to represent a single constraint
Calculate hyperparameters for logit-normal distribution
Generate maximum likelihood estimates of theta
An S4 class to represent a partial credit item
Generate a test cluster object
Calculate probability at a single theta (PC)
Draw an audit trail plot
Generate a test object
Load item paramaters
Draw item information plots
Calculate an EAP estimate of theta for one examinee
An S4 class to represent a test cluster
plotExposureRateFinalFlag
Draw item information plots for flagged items by segment
Load set/stimulus/passage attributes
output_Shadow
Calculate probability at a single theta (1PL)
An S4 class to represent a 1PL item
Overlay item information plots
Create an item pool cluster object
Draw item eligibility statistics plots
Run Test Assembly
Draw an item exposure plot
Create a subset of a test object
Save or print audit trails
An S4 class to represent a 2PL item
Load item attributes
Load constraints
Calculate probability at a single theta (2PL)
Generate maximum likelihood estimates of theta
Draw RMSE plots
Calculate probability at a single theta (3PL)
Calculate probability at a single theta (GPC)
Calculate EAP estimates of theta for a group of examinees
Calculate an empirical Bayes estimate of theta for one examinee
Draw exposure rate plots by final theta segment
plotExposureRateBySegment
Draw exposure rate plots by theta segment
An S4 class to represent a test
Calculate probability at a single theta (GR)
An S4 class to represent a set of constraints.
Create a subset of an item pool object
Calculate a fully Bayesian estimate of theta for a single item
Update constraints
Show constraints
Draw a shadow test chart
An S4 class to represent a cluster of item pools
Simulate item responses
Calculate an empirical Bayes estimate of theta for a single item
Calculate a fully Bayesian estimate of theta for an examinee
Calculate Fisher information at multiple thetas (2PL)
Calculate Fisher information at multiple thetas (1PL)
Run Static Test Assembly
Calculate Root Mean Squared Error
Run adaptive test assembly.
Launch Shiny app
Calculate Relative Errors
Add transparancy to color
Calculate Fisher information at multiple thetas (3PL)