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ltm (version 0.8-9)

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, and the Graded Response Models.

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Version

Install

install.packages('ltm')

Monthly Downloads

8,147

Version

0.8-9

License

GPL (>= 2)

Maintainer

Dimitris Rizopoulos

Last Published

February 18th, 2022

Functions in ltm (0.8-9)

Factor Scores - Ability Estimates

The Law School Admission Test (LSAT), Section VI

Fitted Values for IRT model

Attitude to Science and Technology

Attitude Towards Abortion

Attitude to the Environment

Descriptive Statistics

Cronbach's alpha

Women's Mobility

Extract Estimated Loadings

Anova method for fitted IRT models

Point-Biserial Correlation

Workplace Industrial Relation Survey Data

Goodness of Fit for Rasch Models

Pairwise Associations between Items using a Correlation Coefficient

Factor Scores - Ability Estimates Plot method

Unidimensionality Check using Modified Parallel Analysis

Latent Trait Models for Item Response Theory Analyses

Fit of the model on the margins

Birnbaum's Three Parameter Model

Residuals for IRT models

Item-Fit Statistics and P-values

Plot method for fitted IRT models

vcov method for fitted IRT models

Person-Fit Statistics and P-values

testEquatingData

Prepares Data for Test Equating

Graded Response Model - Polytomous IRT

Latent Trait Model - Latent Variable Model for Binary Data

Generate Random Responses Patterns under Dichotomous IRT models

Multiple Choice Items to Binary Responses

Summary method for fitted IRT models

Area under the Test or Item Information Curves

Descriptive Statistics Plot method