Guidelines for improving statistical analyses of validation datasets for plant pest diagnostic tests

Sebastien Massart*, Benedicte Lebas, Aude Chabirand, Anne Marie Chappé, Tanja Dreo, Francesco Faggioli, Catherine Harrison, Roy Macarthur, Natasha Mehle, Monica Mezzalama, Françoise Petter, Maja Ravnikar, Jean Philippe Renvoisé, Davide Spadaro, Laura Tomassoli, Jenny Tomlinson, Charlotte Trontin, René van der Vlugt, Ana Vučurović, Rebecca WeekesYves Brostaux

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)

Abstract

Appropriate statistical analysis of the validation data for diagnostic tests facilitates the evaluation of the performance criteria and increases the confidence in the conclusions drawn from these data. A comprehensive approach to analysing and reporting data from validation studies and inter-laboratory comparisons such as test performance studies is described. The proposed methods, including statistical analyses, presentation and interpretation of the data, are illustrated using a real dataset generated during a test performance study conducted in the framework of the European project, VALITEST. This analytical approach uses, wherever possible and whenever applicable, statistical analyses recommended by international standards illustrating their application to plant health diagnostic tests. The present work is addressed to plant health diagnosticians and researchers interested and/or involved in the validation of plant diagnostic tests, and also aims to convey the necessary information to those without a statistical background. Detailed statistical explanations are provided in the Appendices.

Original languageEnglish
Pages (from-to)419-433
JournalEPPO Bulletin
Volume52
Issue number2
DOIs
Publication statusPublished - Aug 2022

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