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The PRISMA Statement for Reporting Systematic Reviews and Meta-Analyses of Studies That Evaluate Health Care Interventions: Explanation and Elaboration
TLDR
An Explanation and Elaboration of the PRISMA Statement is presented and updated guidelines for the reporting of systematic reviews and meta-analyses are presented.
The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration
TLDR
The meaning and rationale for each checklist item is explained, and an example of good reporting is included and, where possible, references to relevant empirical studies and methodological literature are included.
Power failure: why small sample size undermines the reliability of neuroscience
TLDR
It is shown that the average statistical power of studies in the neurosciences is very low, and the consequences include overestimates of effect size and low reproducibility of results.
Why Most Published Research Findings Are False
TLDR
Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true.
Genome-wide association studies for complex traits: consensus, uncertainty and challenges
TLDR
This Review highlights the knowledge gained, defines areas of emerging consensus, and describes the challenges that remain as researchers seek to obtain more complete descriptions of the susceptibility architecture of biomedical traits of interest and to translate the information gathered into improvements in clinical management.
The PRISMA Extension Statement for Reporting of Systematic Reviews Incorporating Network Meta-analyses of Health Care Interventions: Checklist and Explanations
TLDR
The process of developing specific advice for the reporting of systematic reviews that incorporate network meta-analyses is described, and the guidance generated from this process is presented.
Redefine statistical significance
TLDR
The default P-value threshold for statistical significance is proposed to be changed from 0.05 to 0.005 for claims of new discoveries in order to reduce uncertainty in the number of discoveries.
Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration
TLDR
In virtually all medical domains, diagnostic and prognostic multivariable prediction models are being developed, validated, updated, and implemented with the aim to assist doctors and individuals in estimating probabilities and potentially influence their decision making.
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