Biomedical research: increasing value, reducing waste

Macleod, Malcolm; Michie, Susan; Roberts, Ian; Dirnagl, Ulrich; Chalmers, Iain; Ioannidis, John P. A.; Salman, Rustam Al-Shahi; Chan, An‐Wen; Glasziou, Paul

doi:10.1016/s0140-6736(13)62329-6

Cited by 809 publications

(669 citation statements)

References 20 publications

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“…In addition, both because of its shortcomings and because it is subject to major misunderstandings it facilitates the production of non-replicable false positive reports. Such reports ultimately erode scientific credibility and result in wasting perhaps most of the research funding in some areas (Ioannidis, 2005;Macleod et al, 2014;Kaplan and Irvin, 2015;Nosek et al, 2015).…”

Section: The State Of the Art Must Change Nhst Is Unsuitable As The Cmentioning

confidence: 99%

When null hypothesis significance testing is unsuitable for research: a reassessment

Szűcs

Ioannidis

2016

Preprint

107

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Null hypothesis significance testing (NHST) has several shortcomings that are likely contributing factors behind the widely debated replication crisis of (cognitive) neuroscience, psychology, and biomedical science in general. We review these shortcomings and suggest that, after sustained negative experience, NHST should no longer be the default, dominant statistical practice of all biomedical and psychological research. If theoretical predictions are weak we should not rely on all or nothing hypothesis tests. Different inferential methods may be most suitable for different types of research questions. Whenever researchers use NHST they should justify its use, and publish pre-study power calculations and effect sizes, including negative findings. Hypothesis-testing studies should be pre-registered and optimally raw data published. The current statistics lite educational approach for students that has sustained the widespread, spurious use of NHST should be phased out.

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Section: The State Of the Art Must Change Nhst Is Unsuitable As The Cmentioning

confidence: 99%

When null hypothesis significance testing is unsuitable for research: a reassessment

Szűcs

Ioannidis

2016

Preprint

107

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“…Ideally, many of these initiatives would include leadership from the patient advocacy organizations relevant to each topic. In this way, the benefits of COS for reducing waste in research will not arise from wasteful practices in their development [48].…”

Section: Expanded Capacity To Produce Cosmentioning

confidence: 99%

Improving the relevance and consistency of outcomes in comparative effectiveness research

et al. 2016

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Policy makers have clearly indicated -through heavy investment in the Patient Centered Outcomes Research Institute -that reporting outcomes that are meaningful to patients is crucial for improvement in healthcare delivery and cost reduction. Better interpretation and generalizability of clinical research results that incorporate patient-centered outcomes research can be achieved by accelerating the development and uptake of core outcome sets (COS). COS provide a standardized minimum set of the outcomes that should be measured and reported in all clinical trials of a specific condition. The level of activity around COS has increased significantly over the past decade, with substantial progress in several clinical domains. However, there are many important clinical conditions for which high-quality COS have not been developed and there are limited resources and capacity with which to develop them. We believe that meaningful progress toward the goals behind the significant investments in patient-centered outcomes research and comparative effectiveness research will depend on a serious effort to address these issues.

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“…In the interest of minimising animal usage and reducing waste in biomedical research, 38,39 researchers should aim to maximise power by designing confirmatory experiments around key questions, use focused hypothesis tests, and avoid dichotomising and nesting that ultimately reduce power and provide no other benefits.…”

Section: Resultsmentioning

confidence: 99%

Four simple ways to increase power without increasing the sample size

Lazic

2017

Preprint

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Underpowered experiments have three problems: the probability of a false positive result is higher, true effects are harder to detect, and the true effects that are detected tend to have inflated effect sizes. Many biology experiments are underpowered and recent calls to change the traditional 0.05 significance threshold to a more stringent value of 0.005 will further reduce the power of the average experiment. Increasing power by increasing the sample size is often the only option considered, but more samples increases costs, makes the experiment harder to conduct, and is contrary to the 3Rs principles for animal research. We show how the design of an experiment and some analytical decisions can have a surprisingly large effect on power.

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Biomedical research: increasing value, reducing waste

Cited by 809 publications

References 20 publications

When null hypothesis significance testing is unsuitable for research: a reassessment

When null hypothesis significance testing is unsuitable for research: a reassessment

Improving the relevance and consistency of outcomes in comparative effectiveness research

Four simple ways to increase power without increasing the sample size

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