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

Autor: Massart, Sebastien, Lebas, Benedicte, Chabirand, Aude, Chappé, Anne Marie, Dreo, Tanja, Faggioli, Francesco, Harrison, Catherine, Macarthur, Roy, Mehle, Natasha, Mezzalama, Monica, Petter, Françoise, Ravnikar, Maja, Renvoisé, Jean Philippe, Spadaro, Davide, Tomassoli, Laura, Tomlinson, Jenny, Trontin, Charlotte, van der Vlugt, René, Vučurović, Ana, Weekes, Rebecca, Brostaux, Yves
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: EPPO Bulletin 52 (2022) 2
EPPO Bulletin, 52(2), 419-433
ISSN: 0250-8052
Popis: 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.
Databáze: OpenAIRE
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