Man pages for philchalmers/mirt
Multidimensional Item Response Theory

anova-methodCompare nested models with likelihood-based statistics
areainfoFunction to calculate the area under a selection of...
averageMICollapse values from multiple imputation draws
bfactorFull-Information Item Bi-factor and Two-Tier Analysis
Bock1997Description of Bock 1997 data
boot.LRParametric bootstrap likelihood-ratio test
boot.mirtCalculate bootstrapped standard errors for estimated models
coef-methodExtract raw coefs from model object
createGroupCreate a user defined group-level object with correct generic...
createItemCreate a user defined item with correct generic functions
deAyalaDescription of deAyala data
DIFDifferential item functioning statistics
DiscreteClass-classClass "DiscreteClass"
DTFDifferential test functioning statistics
empirical_ESEmpirical effect sizes based on latent trait estimates
empirical_plotFunction to generate empirical unidimensional item and test...
empirical_rxxFunction to calculate the empirical (marginal) reliability
estfun.AllModelClassExtract Empirical Estimating Functions
expand.tableExpand summary table of patterns and frequencies
expected.itemFunction to calculate expected value of item
expected.testFunction to calculate expected test score
extract.groupExtract a group from a multiple group mirt object
extract.itemExtract an item object from mirt objects
extract.mirtExtract various elements from estimated model objects
fixefCompute latent regression fixed effect expected values
fscoresCompute factor score estimates (a.k.a, ability estimates,...
imputeMissingImputing plausible data for missing values
itemfitItem fit statistics
itemGAMParametric smoothed regression lines for item response...
iteminfoFunction to calculate item information
itemplotDisplays item surface and information plots
key2binaryScore a test by converting response patterns to binary data
lagrangeLagrange test for freeing parameters
logLik-methodExtract log-likelihood
LSAT6Description of LSAT6 data
LSAT7Description of LSAT7 data
M2Compute the M2 model fit statistic
marginal_rxxFunction to calculate the marginal reliability
MDIFFCompute multidimensional difficulty index
mdirtMultidimensional discrete item response theory
MDISCCompute multidimensional discrimination index
mirtFull-Information Item Factor Analysis (Multidimensional Item...
mirtClusterDefine a parallel cluster object to be used in internal...
mirt.modelSpecify model loadings
mirt-packageFull information maximum likelihood estimation of IRT models.
MixedClass-classClass "MixedClass"
mixedmirtMixed effects modeling for MIRT models
mod2valuesConvert an estimated mirt model to a data.frame
multipleGroupMultiple Group Estimation
MultipleGroupClass-classClass "MultipleGroupClass"
numerical_derivCompute numerical derivatives
personfitPerson fit statistics
PLCI.mirtCompute profiled-likelihood (or posterior) confidence...
plot-methodPlot various test-implied functions from models
poly2dichChange polytomous items to dichotomous item format
print-methodPrint the model objects
print.mirt_dfPrint generic for customized data.frame console output
print.mirt_listPrint generic for customized list console output
print.mirt_matrixPrint generic for customized matrix console output
probtraceFunction to calculate probability trace lines
randefCompute posterior estimates of random effect
residuals-methodCompute model residuals
SAT12Description of SAT12 data
ScienceDescription of Science data
show-methodShow model object
SIBTESTSimultaneous Item Bias Test (SIBTEST)
simdataSimulate response patterns
SingleGroupClass-classClass "SingleGroupClass"
summary-methodSummary of model object
testinfoFunction to calculate test information
vcov-methodExtract parameter variance covariance matrix
waldWald statistics for mirt models
philchalmers/mirt documentation built on Feb. 18, 2018, 2:52 p.m.