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ltm (version 0.9-4)

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

0.9-4

License

GPL (>= 2)

Maintainer

Dimitris Rizopoulos

Last Published

March 16th, 2010

Functions in ltm (0.9-4)

Extract Estimated Loadings

Item-Fit Statistics and P-values

Fitted Values for IRT model

Plot method for fitted IRT models

Graded Response Model - Polytomous IRT

Fit of the model on the margins

Point-Biserial Correlation

Factor Scores - Ability Estimates Plot method

Birnbaum's Three Parameter Model

Summary method for fitted IRT models

Pairwise Associations between Items using a Correlation Coefficient

Latent Trait Models for Item Response Theory Analyses

Attitude to Science and Technology

Area under the Test or Item Information Curves

The Law School Admission Test (LSAT), Section VI

Person-Fit Statistics and P-values

Residuals for IRT models

Goodness of Fit for Rasch Models

Factor Scores - Ability Estimates

Unidimensionality Check using Modified Parallel Analysis

Cronbach's alpha

testEquatingData

Prepares Data for Test Equating

Generalized Partial Credit Model - Polytomous IRT

Latent Trait Model - Latent Variable Model for Binary Data

Workplace Industrial Relation Survey Data

Generate Random Responses Patterns under Dichotomous and Polytomous IRT models

Descriptive Statistics

Attitude to the Environment

Multiple Choice Items to Binary Responses

Descriptive Statistics Plot method

Anova method for fitted IRT models

Women's Mobility

Attitude Towards Abortion

vcov method for fitted IRT models