The co-varying ties between networks and item responses via latent variables

TL;DR

This paper introduces a joint modeling approach to analyze how teachers' advising networks relate to their perceptions, revealing that relationships influence satisfaction and student perceptions more than policy influence, with some schools showing complementary advice-seeking patterns.

Contribution

The paper proposes a novel joint model of network and item responses with correlated latent variables, enabling the analysis of co-varying ties between networks and perceptions.

Findings

Advising relationships impact perceptions of satisfaction and students more than influence.

Complementarity in advice-seeking is observed in certain schools.

The proposed model outperforms separate latent variable models in fit and estimation.

Abstract

Relationships among teachers are known to influence their teaching-related perceptions. We study whether and how teachers' advising relationships (networks) are related to their perceptions of satisfaction, students, and influence over educational policies, recorded as their responses to a questionnaire (item responses). We propose a novel joint model of network and item responses (JNIRM) with correlated latent variables to understand these co-varying ties. This methodology allows the analyst to test and interpret the dependence between a network and item responses. Using JNIRM, we discover that teachers' advising relationships contribute to their perceptions of satisfaction and students more often than their perceptions of influence over educational policies. In addition, we observe that the complementarity principle applies in certain schools, where teachers tend to seek advice from those who are different from them. JNIRM shows superior parameter estimation and model fit over separately modeling the network and item responses with latent variable models.