Psychometrika, the official journal of the Psychometric Society, is devoted to the development of psychology as a quantitative rational science. Articles examine statistical methods, discuss mathematical techniques, and advance theory for evaluating behavioral data in psychology, education, and the social and behavioral sciences generally. There are three main sections in Psychometrika: Theory and Methods, Application Reviews and Case Studies (ARCS), and Book Reviews. Additionally, there is a section online for software, data, and other electronic supplementary material for the articles in these sections.
Theory and Methods is the primary section, and it contains articles that present original research on the development of quantitative models for psychological phenomena, and on quantitative methodology in the social and behavioral sciences, including new mathematical and statistical techniques for the evaluation of psychological data and the application of such techniques.
Application Reviews and Case Studies (ARCS) is the newest section of Psychometrika, and it is designed to highlight the essential connection between data analysis and modelling methodology and its application to data in psychology, education sciences, and related areas in the social sciences and marketing, in a way that deepens the substantive understanding of phenomena in one of these disciplines.
Book Reviews are the third main section of Psychometrika. Book topics include psychometrics, quantitative psychology, and areas in statistics and data mining, as well as substantive areas in psychology, social sciences, etc. that are inspiring for quantitative work in Psychometrika.
Officially cited as: Psychometrika
Ian James Davidson (October 2017)
A New Explanation and Proof of the Paradoxical Scoring Results in Multidimensional Item Response Models
Bayesian Sensitivity Analysis of a Nonlinear Dynamic Factor Analysis Model with Nonparametric Prior and Possible Nonignorable Missingness
- Journal Title
- Volume 1 / 1936 - Volume 82 / 2017
- Print ISSN
- Online ISSN
- Springer US
- Additional Links
- Industry Sectors
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