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ltm (version 0.9-1)

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

0.9-1

License

GPL (>= 2)

Maintainer

Dimitris Rizopoulos

Last Published

June 19th, 2009

Functions in ltm (0.9-1)

Item-Fit Statistics and P-values

Factor Scores - Ability Estimates

Graded Response Model - Polytomous IRT

Latent Trait Models for Item Response Theory Analyses

Anova method for fitted IRT models

Residuals for IRT models

Generalized Partial Credit Model - Polytomous IRT

Attitude Towards Abortion

Point-Biserial Correlation

Goodness of Fit for Rasch Models

Fit of the model on the margins

Descriptive Statistics

Attitude to the Environment

Area under the Test or Item Information Curves

Generate Random Responses Patterns under Dichotomous and Polytomous IRT models

Birnbaum's Three Parameter Model

Extract Estimated Loadings

Cronbach's alpha

Latent Trait Model - Latent Variable Model for Binary Data

Factor Scores - Ability Estimates Plot method

Attitude to Science and Technology

Plot method for fitted IRT models

The Law School Admission Test (LSAT), Section VI

Summary method for fitted IRT models

Fitted Values for IRT model

Women's Mobility

Pairwise Associations between Items using a Correlation Coefficient

Person-Fit Statistics and P-values

Descriptive Statistics Plot method

Workplace Industrial Relation Survey Data

testEquatingData

Prepares Data for Test Equating

Multiple Choice Items to Binary Responses

Unidimensionality Check using Modified Parallel Analysis

vcov method for fitted IRT models