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How measurement science can improve confidence in research results

The current push for rigor and reproducibility is driven by a desire for confidence in research results. Here, we suggest a framework for a systematic process, based on consensus principles of measurement science, to guide researchers and reviewers in assessing, documenting, and mitigating the sourc...

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Detalles Bibliográficos
Autores principales: Plant, Anne L., Becker, Chandler A., Hanisch, Robert J., Boisvert, Ronald F., Possolo, Antonio M., Elliott, John T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5933802/
https://www.ncbi.nlm.nih.gov/pubmed/29684013
http://dx.doi.org/10.1371/journal.pbio.2004299
Descripción
Sumario:The current push for rigor and reproducibility is driven by a desire for confidence in research results. Here, we suggest a framework for a systematic process, based on consensus principles of measurement science, to guide researchers and reviewers in assessing, documenting, and mitigating the sources of uncertainty in a study. All study results have associated ambiguities that are not always clarified by simply establishing reproducibility. By explicitly considering sources of uncertainty, noting aspects of the experimental system that are difficult to characterize quantitatively, and proposing alternative interpretations, the researcher provides information that enhances comparability and reproducibility.