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