Reproducibility: The EQUATOR Network and reporting guidelines

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Increasing awareness of the lack of reproducibility in research has prompted many scientists and other professionals to develop strategies to improve research reproducibility. One key reason why there is so much waste in biomedical research is because many reports of research are incomplete or inaccurate. One group that has endeavoured improve the reporting of health research by developing reporting guidelines

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Minimising false positives and false negatives in research

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In December 2016, the Journal of Applied Physiology commenced the series Cores of Reproducibility in Physiology (CORP) to highlight the lack of reproducibliity in physiology research and provide solutions. In the first CORP article, statistician Dogulas Curran-Everett explains that to improve reproducibility in research, experiments and analyses need to minimise false positive and false negative findings. The false positive rate

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P values and hypothesis tests cannot indicate the size or precision of effects

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P values and hypothesis testing methods are frequently misused in clinical and experimental research, perhaps because of the misconception that they provide simple, objective tools to separate true from untrue facts. In a new paper, the cardiologist Daniel Mark and statisticians Kerry Lee and Frank Harrell explain the role and limitations of p values and hypothesis tests in clinical research.

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Strategies to improve research reproducibility

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I recently highlighted a symposium that was held to improve the reproducibility of biomedical research. The published report includes a discussion on strategies that can help improve research practice and research reproducibility. Statistics: continuing education opportunities Stakeholders at the conference highlighted the need for continuing education opportunities in statistics. Continuing education should focus on examples and case studies that are

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