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ltm (version 0.9-7)

Latent Trait Models under IRT

Description

Analysis of multivariate dichotomous and polytomous data using latent trait models under the Item Response Theory approach. It includes the Rasch, the Two-Parameter Logistic, the Birnbaum's Three-Parameter, the Graded Response, and the Generalized Partial Credit Models.

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Version

Install

install.packages('ltm')

Monthly Downloads

6,237

Version

0.9-7

License

GPL (>= 2)

Maintainer

Dimitris Rizopoulos

Last Published

October 18th, 2011

Functions in ltm (0.9-7)

anova

Anova method for fitted IRT models
item.fit

Item-Fit Statistics and P-values
grm

Graded Response Model - Polytomous IRT
Environment

Attitude to the Environment
rasch

Rasch Model
Abortion

Attitude Towards Abortion
fitted

Fitted Values for IRT model
person.fit

Person-Fit Statistics and P-values
WIRS

Workplace Industrial Relation Survey Data
residuals

Residuals for IRT models
plot fscores

Factor Scores - Ability Estimates Plot method
ltm

Latent Trait Model - Latent Variable Model for Binary Data
information

Area under the Test or Item Information Curves
descript

Descriptive Statistics
factor.scores

Factor Scores - Ability Estimates
summary

Summary method for fitted IRT models
vcov

vcov method for fitted IRT models
tpm

Birnbaum's Three Parameter Model
unidimTest

Unidimensionality Check using Modified Parallel Analysis
cronbach.alpha

Cronbach's alpha
plot descript

Descriptive Statistics Plot method
coef

Extract Estimated Loadings
gpcm

Generalized Partial Credit Model - Polytomous IRT
rmvlogis

Generate Random Responses Patterns under Dichotomous and Polytomous IRT models
testEquatingData

Prepares Data for Test Equating
Mobility

Women's Mobility
Science

Attitude to Science and Technology
gh

Gauss-Hermite Quadrature Points
ltm-package

Latent Trait Models for Item Response Theory Analyses
plot IRT

Plot method for fitted IRT models
rcor.test

Pairwise Associations between Items using a Correlation Coefficient
biserial.cor

Point-Biserial Correlation
GoF

Goodness of Fit for Rasch Models
LSAT

The Law School Admission Test (LSAT), Section VI
mult.choice

Multiple Choice Items to Binary Responses
margins

Fit of the model on the margins