Cargando…

RIPOSTE: a framework for improving the design and analysis of laboratory-based research

Lack of reproducibility is an ongoing problem in some areas of the biomedical sciences. Poor experimental design and a failure to engage with experienced statisticians at key stages in the design and analysis of experiments are two factors that contribute to this problem. The RIPOSTE (Reducing IrreP...

Descripción completa

Detalles Bibliográficos
Autores principales: Masca, Nicholas GD, Hensor, Elizabeth MA, Cornelius, Victoria R, Buffa, Francesca M, Marriott, Helen M, Eales, James M, Messenger, Michael P, Anderson, Amy E, Boot, Chris, Bunce, Catey, Goldin, Robert D, Harris, Jessica, Hinchliffe, Rod F, Junaid, Hiba, Kingston, Shaun, Martin-Ruiz, Carmen, Nelson, Christopher P, Peacock, Janet, Seed, Paul T, Shinkins, Bethany, Staples, Karl J, Toombs, Jamie, Wright, Adam KA, Teare, M Dawn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4461852/
https://www.ncbi.nlm.nih.gov/pubmed/25951517
http://dx.doi.org/10.7554/eLife.05519
Descripción
Sumario:Lack of reproducibility is an ongoing problem in some areas of the biomedical sciences. Poor experimental design and a failure to engage with experienced statisticians at key stages in the design and analysis of experiments are two factors that contribute to this problem. The RIPOSTE (Reducing IrreProducibility in labOratory STudiEs) framework has been developed to support early and regular discussions between scientists and statisticians in order to improve the design, conduct and analysis of laboratory studies and, therefore, to reduce irreproducibility. This framework is intended for use during the early stages of a research project, when specific questions or hypotheses are proposed. The essential points within the framework are explained and illustrated using three examples (a medical equipment test, a macrophage study and a gene expression study). Sound study design minimises the possibility of bias being introduced into experiments and leads to higher quality research with more reproducible results. DOI: http://dx.doi.org/10.7554/eLife.05519.001