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ltm (version 0.9-2)

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

6,099

Version

0.9-2

License

GPL (>= 2)

Maintainer

Dimitris Rizopoulos

Last Published

October 12th, 2009

Functions in ltm (0.9-2)

Descriptive Statistics

Birnbaum's Three Parameter Model

Area under the Test or Item Information Curves

Residuals for IRT models

Generate Random Responses Patterns under Dichotomous and Polytomous IRT models

Cronbach's alpha

Unidimensionality Check using Modified Parallel Analysis

Person-Fit Statistics and P-values

Attitude to the Environment

Goodness of Fit for Rasch Models

Women's Mobility

Item-Fit Statistics and P-values

Workplace Industrial Relation Survey Data

Factor Scores - Ability Estimates

Graded Response Model - Polytomous IRT

Descriptive Statistics Plot method

Fit of the model on the margins

The Law School Admission Test (LSAT), Section VI

Attitude to Science and Technology

Plot method for fitted IRT models

Latent Trait Models for Item Response Theory Analyses

vcov method for fitted IRT models

Pairwise Associations between Items using a Correlation Coefficient

Attitude Towards Abortion

Factor Scores - Ability Estimates Plot method

Summary method for fitted IRT models

testEquatingData

Prepares Data for Test Equating

Multiple Choice Items to Binary Responses

Generalized Partial Credit Model - Polytomous IRT

Point-Biserial Correlation

Latent Trait Model - Latent Variable Model for Binary Data

Anova method for fitted IRT models

Extract Estimated Loadings

Fitted Values for IRT model