Cargando…
Improving reproducibility by using high-throughput observational studies with empirical calibration
Concerns over reproducibility in science extend to research using existing healthcare data; many observational studies investigating the same topic produce conflicting results, even when using the same data. To address this problem, we propose a paradigm shift. The current paradigm centres on genera...
Autores principales: | Schuemie, Martijn J., Ryan, Patrick B., Hripcsak, George, Madigan, David, Suchard, Marc A. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society Publishing
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6107542/ https://www.ncbi.nlm.nih.gov/pubmed/30082302 http://dx.doi.org/10.1098/rsta.2017.0356 |
Ejemplares similares
-
Robust empirical calibration of p‐values using observational data
por: Schuemie, Martijn J., et al.
Publicado: (2016) -
Drawing Reproducible Conclusions from Observational Clinical Data with OHDSI
por: Hripcsak, George, et al.
Publicado: (2021) -
Interpreting observational studies: why empirical calibration is needed to correct p-values
por: Schuemie, Martijn J, et al.
Publicado: (2014) -
Adjusting for both sequential testing and systematic error in safety surveillance using observational data: Empirical calibration and MaxSPRT
por: Schuemie, Martijn J., et al.
Publicado: (2023) -
Principles of Large-scale Evidence Generation and Evaluation across a Network of Databases (LEGEND)
por: Schuemie, Martijn J, et al.
Publicado: (2020)