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mirt (version 1.8)

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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Version

Install

install.packages('mirt')

Monthly Downloads

9,054

Version

1.8

License

GPL (>= 3)

Issues

0

Pull Requests

0

Stars

224

Forks

79

Maintainer

Phil Chalmers

Last Published

January 22nd, 2015

Functions in mirt (1.8)

MixedClass-class

Class "MixedClass"
boot.mirt

Calculate bootstrapped standard errors for estimated models
expected.item

Function to calculate expected value of item
Bock1997

Description of Bock 1997 data
DiscreteClass-class

Class "DiscreteClass"
mirt.model

Specify model loadings
SAT12

Description of SAT12 data
probtrace

Function to calculate probability trace lines
mirt-package

Full information maximum likelihood estimation of IRT models.
plot-method

Plot various test implied functions from models
M2

Compute M2 statistic
bfactor

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

Person fit statistics
mod2values

Convert an estimated mirt model to special data.frame
Science

Description of Science data
mixedmirt

Mixed effects modeling for MIRT models
show-method

Show model object
LSAT7

Description of LSAT7 data
fscores

Methods for Function fscores
PLCI.mirt

Compute profiled-likelihood confidence intervals
imputeMissing

Imputing plausible data for missing values
extract.group

Extract a group from a multiple group mirt object
summary-method

Summary of model object
key2binary

Convert response patterns to binary data
simdata

Simulate response patterns
LSAT6

Description of LSAT6 data
coef-method

Extract raw coefs from model object
multipleGroup

Multiple Group Estimation
testinfo

Function to calculate test information
SingleGroupClass-class

Class "SingleGroupClass"
averageMI

Collapse values from multiple imputation draws
deAyala

Description of deAyala data
anova-method

Compare nested models
DTF

Differential test functioning
createItem

Create a user defined item with correct generic functions
DIF

Differential item functioning tests
itemplot

Displays item surface and information plots
mirtCluster

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

Wald test for mirt models
expand.table

Expand summary table of patterns and frequencies
expected.test

Function to calculate expected test score
print-method

Print the model objects
iteminfo

Function to calculate item information
randef

Compute random effects
mdirt

Multidimensional discrete item response theory
MultipleGroupClass-class

Class "MultipleGroupClass"
extract.item

Extract an item object from mirt objects
residuals-method

Compute model residuals
mirt

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

Item fit statistics