R: Multidimensional Item Response Theory

# Multidimensional Item Response Theory

## Documentation for package ‘mirt’ version 1.47

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

mirt-package | Full information maximum likelihood estimation of IRT models.
anova-method | Compare nested models with likelihood-based statistics
areainfo | Function to calculate the area under a selection of information curves
ASVAB | Description of ASVAB data
Attitude | Description of Attitude data
averageMI | Collapse values from multiple imputation draws
bfactor | Full-Information Item Bi-factor and Two-Tier Analysis
Bock1997 | Description of Bock 1997 data
boot.LR | Parametric bootstrap likelihood-ratio test
boot.mirt | Calculate bootstrapped standard errors for estimated models
coef-method | Extract raw coefs from model object
createGroup | Create a user defined group-level object with correct generic functions
createItem | Create a user defined item with correct generic functions
deAyala | Description of deAyala data
DeltaMethod | Numerical derivative version of delta method
DIF | Differential item functioning statistics
DiscreteClass-class | Class "DiscreteClass"
draw_parameters | Draw plausible parameter instantiations from a given model
DRF | Differential Response Functioning statistics
DTF | Differential test functioning statistics
empirical_ES | Empirical effect sizes based on latent trait estimates
empirical_plot | Function to generate empirical unidimensional item and test plots
empirical_rxx | Function to calculate the empirical (marginal) reliability
estfun.AllModelClass | Extract Empirical Estimating Functions
expand.table | Expand summary table of patterns and frequencies
expected.item | Function to calculate expected value of item
expected.test | Function to calculate expected test score
extract.group | Extract a group from a multiple group mirt object
extract.item | Extract an item object from 'mirt' objects
extract.mirt | Extract various elements from estimated model objects
fixedCalib | Fixed-item calibration method
fixef | Compute latent regression fixed effect expected values
fscores | Compute factor score estimates (a.k.a, ability estimates, latent trait estimates, etc)
gen.difficulty | Generalized item difficulty summaries
head.mirt_matrix | Head generic for customized matrix console output
imputeMissing | Imputing plausible data for missing values
itemfit | Item fit statistics
itemGAM | Parametric smoothed regression lines for item response probability functions
iteminfo | Function to calculate item information
itemplot | Displays item surface and information plots
itemstats | Generic item summary statistics
key2binary | Score a test by converting response patterns to binary data
lagrange | Lagrange test for freeing parameters
likert2int | Convert ordered Likert-scale responses (character or factors) to integers
logLik-method | Extract log-likelihood
LSAT6 | Description of LSAT6 data
LSAT7 | Description of LSAT7 data
M2 | Compute the M2 model fit statistic
marginal_moments | Function to calculate the marginal moments for items and bundles fit via IRT models
marginal_rxx | Function to calculate the marginal reliability
MDIFF | Compute multidimensional difficulty index
mdirt | Multidimensional discrete item response theory
MDISC | Compute multidimensional discrimination index
mirt | Full-Information Item Factor Analysis (Multidimensional Item Response Theory)
mirt.model | Specify model information
mirtCluster | Define a parallel cluster object to be used in internal functions
MixedClass-class | Class "MixedClass"
mixedmirt | Mixed effects modeling for MIRT models
MixtureClass-class | Class "MixtureClass"
mod2values | Convert an estimated mirt model to a data.frame
multipleGroup | Multiple Group Estimation
MultipleGroupClass-class | Class "MultipleGroupClass"
numerical_deriv | Compute numerical derivatives
personfit | Person fit statistics
pirt | Projective IRT (PIRT) models
pirt_DIF | Simulated datasets for PIRT-DIF
PLCI.mirt | Compute profiled-likelihood (or posterior) confidence intervals
plot-method | Plot various test-implied functions from models
plot.itemGAM | Parametric smoothed regression lines for item response probability functions
poly2dich | Change polytomous items to dichotomous item format
print-method | Print the model objects
print.matrix | Print generic for customized matrix console output
print.mirt_df | Print generic for customized data.frame console output
print.mirt_list | Print generic for customized list console output
print.mirt_matrix | Print generic for customized matrix console output
probtrace | Function to calculate probability trace lines
randef | Compute posterior estimates of random effect
RCI | Model-based Reliable Change Index
read.mirt | Translate mirt parameters into suitable structure for plink package
remap.distance | Remap item categories to have integer distances of 1
residuals-method | Compute model residuals
reverse.score | Reverse score one or more items from a response matrix
RMSD_DIF | RMSD effect size statistic to quantify category-level DIF
SAT12 | Description of SAT12 data
Science | Description of Science data
secondOrderTest | Second-order test of convergence
show-method | Show model object
SIBTEST | (Generalized) Simultaneous Item Bias Test (SIBTEST)
simdata | Simulate response patterns
SingleGroupClass-class | Class "SingleGroupClass"
SLF | Social Life Feelings Data
summary-method | Summary of model object
tail.mirt_matrix | Tail generic for customized matrix console output
testinfo | Function to calculate test information
thetaComb | Create all possible combinations of vector input
traditional2mirt | Convert traditional IRT metric into slope-intercept form used in mirt
vcov-method | Extract parameter variance covariance matrix
wald | Wald statistics for mirt models