A Java library for psychometric analysis. View the psychometrics API to learn more about the library. It includes mathematical and statistical procedures that are not part of the Apache commons math library. It is a key component of jMetrik an open source application for psychometrics. See http://www.ItemAnalysis.com for more information about jMetrik and the psychometrics library.

Recommended Citation:

Meyer, J. P. (2015). Psychometrics: An open source Java^TM library for measurement [computer software]. Available from https://github.com/meyerjp3/psychometrics.

The library is licensed under the Apache License, Version 2.0.

This library provides classes for IRT parameter estimation, scale linking, and score equating. Estimation currently involves joint maximum likelihood for the Rasch, partial credit, and rating scale models. Marginal maximum likelihood estimation procedures for binary item response models (Rasch, 2PL, 3PL, 4PL) and polytomous item response models (GPCM, PCM) are also available. Scale linking and score equating classes support a variety of item response models. Scale linking procedures available in the library include the Stocking-Lord and Haebara procedures.

Classes for exploratory factor analysis are in development. They currently include MINRES factor analysis and principal components analysis. Some rotations have been implemented.

The library includes classes for classical test scaling methods, reliability estimation, item analysis, and differential item functioning (DIF). Examples of scaling methods include normalized scores and Kelley's regressed score. Reliability methods include Coefficient alpha Guttman's lambda, and other methods. There are classes to support the conditional standard error of measurement and decision consistency indices. Classes that support DIF include the Cochran-Mantel-Haenszel procedure and ETS DIF classification levels.