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

arXiv: https://arxiv.org/abs/2409.19400 · HTML: https://mlsanity.com/paper/2409.19400/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 5 of its 59 references that are in the map.
- First posted on arXiv 28 Sep 2024.

## Builds on (most cited first, 5 of 5)

- [A Mutually Exciting Latent Space Hawkes Process Model for Continuous-time Networks](https://mlsanity.com/paper/2205.09263/) (2022)
- [Additive and multiplicative effects network models](https://mlsanity.com/paper/1807.08038/) (2018)
- [Spectral inference for large Stochastic Blockmodels with nodal covariates](https://mlsanity.com/paper/1908.06438/) (2019)
- [Testing and Modeling Dependencies Between a Network and Nodal Attributes](https://mlsanity.com/paper/1306.4708/) (2013)
- [Dyadic data analysis with amen](https://mlsanity.com/paper/1506.08237/) (2015)

## Abstract (arXiv)

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.