A Collection of Functions Related to Item Response Theory (IRT)
Estimate ability
The api appropriateness index
Draw plausible values
EAP estimation of ability
Plot empirical response function
Estimate item parameters
Item information function
Interaction model
Item response function
Item fit plot
Estimate and plot IRT models for binary responses
Test item fit
Maximum likelihood and Bayes Modal estimation of ability
Normal quadrature points and weights
Non-parametric characteristic curves
A plot method for item information functions
A plot method for the interaction model
A plot method for item response functions
A plot method for test information functions
A plot method for test response functions
Quantiles of the ranked sum scores
Read in parameter estimates
Read in parameter estimates
Read in quadrature
Read responses from a file
Item-total regressions for the Rasch vs. the interaction model
Linear transformation of the IRT scale
Score a multiple choice test
Sum score metric
Plot observed and predicted scores against ability
Simulate response data
Approximate tetchoric correlation matrix
Non-parametric option curves
Elementary test-item analysis
Test information function
Test response function
True scores with standard errors
Bias-corrected (Warm's) estimates of ability
A collection of functions useful in learning and practicing IRT, which can be combined into larger programs. Provides basic CTT analysis, a simple common interface to the estimation of item parameters in IRT models for binary responses with three different programs (ICL, BILOG-MG, and ltm), ability estimation (MLE, BME, EAP, WLE, plausible values), item and person fit statistics, scaling methods (MM, MS, Stocking-Lord, and the complete Hebaera method), and a rich array of parametric and non-parametric (kernel) plots. Estimates and plots Haberman's interaction model when all items are dichotomously scored.