Calculate bootstrapped standard errors for estimated models
Item fit statistics
Description of Bock 1997 data
Methods for Function fscores
Create a user defined item with correct generic functions
Class "ExploratoryClass"
Differential item functioning tests
Class "ConfirmatoryClass"
Expand summary table of patterns and frequencies
Class "MultipleGroupClass"
Compute Extra Model Fit Indices
Multiple Group Estimation
Function to calculate expected value of item
Convert an estimated mirt model to special data.frame
Class "SingleGroupClass"
Description of LSAT6 data
Compute profiled-likelihood confidence intervals
Wald test for mirt models
Monte Carlo Log-Likelihood Calculation
Person fit statistics
Compute fitted values
Description of deAyala data
Description of LSAT7 data
Print the model objects
Specify model loadings
Function to calculate item information
Full-Information Item Factor Analysis (Multidimensional Item Response
Theory)
Compute random effects
Class "DiscreteClass"
Description of Science data
Mixed effects modeling for MIRT models
Differential test functioning statistics
Parametric smoothed regression lines for item response probability functions
Compare nested models with likelihood-based statistics
Plot various test implied functions from models
Extract raw coefs from model object
Extract an item object from mirt objects
Full-Information Item Bi-factor and Two-Tier Analysis
Description of SAT12 data
Full information maximum likelihood estimation of IRT models.
Displays item surface and information plots
Class "MixedClass"
Compute multidimensional discrimination index
Imputing plausible data for missing values
Translate mirt parameters for plink package
Compute multidimensional difficulty index
Define a parallel cluster object to be used in internal functions
Function to calculate probability trace lines
Summary of model object
Extract a group from a multiple group mirt object
Simulate response patterns
Function to calculate the marginal reliability
Function to calculate expected test score
Compute model residuals
Compute the M2 model fit statistic
Function to calculate test information
Compute latent regression fixed effect expected values
Multidimensional discrete item response theory
Score a test by converting response patterns to binary data
Show model object
Collapse values from multiple imputation draws
Simultaneous Item Bias Test (SIBTEST)
Function to calculate the empirical (marginal) reliability
Extract various elements from estimated model objects
Function to calculate the area under a selection of information curves
Lagrange test for freeing parameters
Extract log-likelihood
Function to generate empirical unidimensional item and test plots
Extract parameter variance covariance matrix
Compute numerical derivatives
Empirical effect sizes based on latent trait estimates