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Protocol for development of a checklist and guideline for transparent reporting of cluster analyses (TRoCA)
0
Zitationen
19
Autoren
2025
Jahr
Abstract
INTRODUCTION: Cluster analysis, a machine learning-based and data-driven technique for identifying groups in data, has demonstrated its potential in a wide range of contexts. However, critical appraisal and reproducibility are often limited by insufficient reporting, ultimately hampering the interpretation and trust of key stakeholders. The present paper describes the protocol that will guide the development of a reporting guideline and checklist for studies incorporating cluster analyses-Transparent Reporting of Cluster Analyses. METHODS AND ANALYSIS: =≈) to derive consensus regarding items in the checklist and piloting of the checklist. Stage 5: consensus meeting to consolidate checklist. Stage 6: production of statement paper and explanation and elaboration paper. Stage 7: dissemination via journals, conferences, social media and a dedicated web platform. ETHICS AND DISSEMINATION: Due to local regulations, the planned study is exempt from the requirement of ethical review. The findings will be disseminated through peer-reviewed publications. The checklist with explanations will also be made available freely on a dedicated web platform (troca-statement.org) and in a repository.
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Autoren
- Daniil Lisik
- Syed Ahmar Shah
- Rani Basna
- Duy-Tai Dinh
- Ryan P. Browne
- Jeffrey L. Andrews
- Meredith L. Wallace
- Absalom E. Ezugwu
- Ana Marušić
- Dat Tran
- Joaquín Torres-Sospedra
- Hieu‐Chi Dam
- Philippe Fournier‐Viger
- Christian Hennig
- Marieke E. Timmerman
- Matthijs J. Warrens
- Eva Ceulemans
- Bright I. Nwaru
- Tina Hernandez‐Boussard
Institutionen
- University of Gothenburg(SE)
- Umeå University(SE)
- University of Edinburgh(GB)
- Lund University(SE)
- Kyoto College of Graduate Studies for Informatics(JP)
- University of Waterloo(CA)
- University of British Columbia(CA)
- University of Pittsburgh(US)
- North-West University(ZA)
- University of Split(HR)
- University of Canberra(AU)
- ACT Government
- Universitat de València(ES)
- Japan Advanced Institute of Science and Technology(JP)
- Shenzhen Research Institute of Big Data(CN)
- University of Bologna(IT)
- University of Groningen(NL)
- KU Leuven(BE)
- Wallenberg Wood Science Center(SE)
- Stanford University(US)