tna: An R Package for Transition Network Analysis

Abstract

Understanding the dynamics of transitions plays a central role in educational research, informing studies of learning processes, motivation shifts, and social interactions. Transition network analysis (TNA) is a unified framework of probabilistic modeling and network analysis for capturing the temporal and relational aspects of transitions between events or states of interest. We introduce the R package tna that implements procedures for estimating the TNA models, building the transition networks, identifying patterns and communities, computing centrality measures, and visualizing the networks. The package also implements several functions for statistical procedures that can be used to assess differences between groups, stability of centrality measures and importance of specific transitions. © The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).