Network Psychometrics

TL;DR

This chapter introduces network modeling in psychometrics, focusing on the Ising model's formulation, its equivalence to psychometric models, and implications for interpreting latent variables.

Contribution

It establishes the connection between the Ising model and psychometric models like MIRT, providing new insights into latent variable interpretation.

Findings

Ising model is equivalent to certain logistic regression and MIRT models

Methods for estimating the Ising model are overviewed

The interpretation of latent variables is reexamined through model equivalence

Abstract

This chapter provides a general introduction of network modeling in psychometrics. The chapter starts with an introduction to the statistical model formulation of pairwise Markov random fields (PMRF), followed by an introduction of the PMRF suitable for binary data: the Ising model. The Ising model is a model used in ferromagnetism to explain phase transitions in a field of particles. Following the description of the Ising model in statistical physics, the chapter continues to show that the Ising model is closely related to models used in psychometrics. The Ising model can be shown to be equivalent to certain kinds of logistic regression models, loglinear models and multi-dimensional item response theory (MIRT) models. The equivalence between the Ising model and the MIRT model puts standard psychometrics in a new light and leads to a strikingly different interpretation of well-known latent variable models. The chapter gives an overview of methods that can be used to estimate the Ising model, and concludes with a discussion on the interpretation of latent variables given the equivalence between the Ising model and MIRT.