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mirt (version 1.9)

Multidimensional Item Response Theory

Description

Analysis of dichotomous and polytomous response data using unidimensional and multidimensional latent trait models under the Item Response Theory paradigm. Exploratory and confirmatory models can be estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory bi-factor and two-tier analyses are available for modeling item testlets. Multiple group analysis and mixed effects designs also are available for detecting differential item functioning and modelling item and person covariates.

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Install

install.packages('mirt')

Monthly Downloads

9,054

Version

1.9

License

GPL (>= 3)

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Maintainer

Phil Chalmers

Last Published

March 29th, 2015

Functions in mirt (1.9)

M2

Compute M2 statistic
DIF

Differential item functioning tests
mirt-package

Full information maximum likelihood estimation of IRT models.
DiscreteClass-class

Class "DiscreteClass"
expand.table

Expand summary table of patterns and frequencies
DTF

Differential test functioning
deAyala

Description of deAyala data
extract.group

Extract a group from a multiple group mirt object
boot.mirt

Calculate bootstrapped standard errors for estimated models
simdata

Simulate response patterns
fscores

Methods for Function fscores
testinfo

Function to calculate test information
anova-method

Compare nested models
createItem

Create a user defined item with correct generic functions
SingleGroupClass-class

Class "SingleGroupClass"
probtrace

Function to calculate probability trace lines
plot-method

Plot various test implied functions from models
wald

Wald test for mirt models
show-method

Show model object
Science

Description of Science data
mirt.model

Specify model loadings
print-method

Print the model objects
mod2values

Convert an estimated mirt model to special data.frame
personfit

Person fit statistics
multipleGroup

Multiple Group Estimation
expected.item

Function to calculate expected value of item
randef

Compute random effects
mirtCluster

Define a parallel cluster object to be used in internal functions
Bock1997

Description of Bock 1997 data
mirt

Full-Information Item Factor Analysis (Multidimensional Item Response Theory)
iteminfo

Function to calculate item information
extract.item

Extract an item object from mirt objects
MixedClass-class

Class "MixedClass"
coef-method

Extract raw coefs from model object
imputeMissing

Imputing plausible data for missing values
itemfit

Item fit statistics
mixedmirt

Mixed effects modeling for MIRT models
mdirt

Multidimensional discrete item response theory
SAT12

Description of SAT12 data
bfactor

Full-Information Item Bi-factor and Two-Tier Analysis
averageMI

Collapse values from multiple imputation draws
summary-method

Summary of model object
PLCI.mirt

Compute profiled-likelihood confidence intervals
LSAT7

Description of LSAT7 data
LSAT6

Description of LSAT6 data
key2binary

Convert response patterns to binary data
itemplot

Displays item surface and information plots
expected.test

Function to calculate expected test score
MultipleGroupClass-class

Class "MultipleGroupClass"
fixef

Compute latent regression fixed effects
residuals-method

Compute model residuals