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tna: An R Package for Transition Network Analysis

Santtu Tikka et al.

Applied Psychological Measurement2025https://doi.org/10.1177/01466216251348840article
AJG 2ABDC B
Weight
0.52

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.

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https://doi.org/https://doi.org/10.1177/01466216251348840

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@article{santtu2025,
  title        = {{tna: An R Package for Transition Network Analysis}},
  author       = {Santtu Tikka et al.},
  journal      = {Applied Psychological Measurement},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1177/01466216251348840},
}

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tna: An R Package for Transition Network Analysis

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Evidence weight

0.52

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.47 × 0.4 = 0.19
M · momentum0.68 × 0.15 = 0.10
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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