Evidence map›Paper›PMID 40486723›Full record

ArticleApplied psychological measurement2025

tna: An R Package for Transition Network Analysis.

Santtu Tikka, Sonsoles López-Pernas, Mohammed Saqr

Abstract read
In one paragraph

Article in Applied psychological measurement, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. tna: An R Package for Transition Network Analysis.Applied psychological measurement · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Santtu TikkaUniversity of Jyväskylä, Jyväskylä, Finland.ORCID https://orcid.org/0000-0003-4039-4342
Sonsoles López-PernasUniversity of Eastern Finland, Joensuu, Finland.ORCID https://orcid.org/0000-0002-9621-1392
Mohammed SaqrUniversity of Eastern Finland, Joensuu, Finland.ORCID https://orcid.org/0000-0001-5881-3109

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

complex dynamic systemslearning analyticsMarkov modelsR packagesequence analysissocial network analysistnatransition network analysis

Identifiers

PMID40486723
PMCPMC12141252

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.