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Evaluating a shrinkage estimator for the treatment effect in clinical trials
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Evaluating a shrinkage estimator for the treatment effect in clinical trials (2023)Evaluating a shrinkage estimator for the …How large should the next study be? Predictive power and sample size requirements for replication studies (2022)How large should the next stu…The statistical properties of RCTs and a proposal for shrinkage (2021)The statistical properties of…Assessing treatment effects and publication bias across different specialties in medicine: a meta-epidemiological study (2021)Assessing treatment effects a…Addressing Exaggeration of Effects from Single RCTs (2021)Addressing Exaggeration of Ef…Low statistical power in biomedical science: a review of three human research domains (2017)Low statistical power in biom…Beyond Power Calculations (2014)Beyond Power CalculationsPower failure: why small sample size undermines the reliability of neuroscience (2013)Power failure: why small samp…Characteristics of meta-analyses and their component studies in the Cochrane Database of Systematic Reviews: a cross-sectional, descriptive analysis (2011)Characteristics of meta-analy…Conducting Meta-Analyses in R with the metafor Package (2010)Conducting Meta-Analyses in R…Why Most Discovered True Associations Are Inflated (2008)Why Most Discovered True Asso…The cochrane database of systematic reviews (1996)Measuring inconsistency in meta-analyses (2003)A Re-Evaluation of Random-Effects Meta-Analysis (2008)A taxonomy has been developed for outcomes in medical research to help improve knowledge discovery (2017)Built environmental correlates of older adults’ total physical activity and walking: a systematic review and meta-analysis (2017)The neighbourhood physical environment and active travel in older adults: a systematic review and meta-analysis (2017)Why Most Published Research Findings Are False (2005)G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences (2007)Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials (2011)Meta-analysis and the science of research synthesis (2018)Sample Size Justification (2022)False-Positive Psychology (2011)Scientific Utopia (2012)Is psychology suffering from a replication crisis? What does “failure to replicate” really mean? (2015)Preferred reporting items for systematic reviews and meta‐analyses in ecology and evolutionary biology: a PRISMA extension (2021)Replicability, Robustness, and Reproducibility in Psychological Science (2021)Meta-analysis in clinical trials (1986)Bias in meta-analysis detected by a simple, graphical test (1997)Quantifying heterogeneity in a meta‐analysis (2002)How to perform a meta-analysis with R: a practical tutorial (2019)PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews (2021)The Revised CONSORT Statement for Reporting Randomized Trials: Explanation and Elaboration (2001)Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration (2007)How Big Is “Big”? Interpreting Effect Sizes in L2 Research (2014)Increasing value and reducing waste in research design, conduct, and analysis (2014)Choosing Prediction Over Explanation in Psychology: Lessons From Machine Learning (2017)Contradicted and Initially Stronger Effects in Highly Cited Clinical Research (2005)Introducing a new “ Preliminary Report” submission category for small-sample intervention studies: rationale and instructions (2025)Cochrane Handbook for Systematic Reviews of Interventions (2008)Spin and fragility in randomised controlled trials in the anaesthesia literature: a systematic review (2023)Publication bias in meta‐analyses from the Cochrane Database of Systematic Reviews (2015)Forcing a Deterministic Frame on Probabilistic Phenomena: A Communication Blind Spot in Media Coverage of the “Replication Crisis” (2024)Estimating the reproducibility of psychological science (2015)A large-scale in silico replication of ecological and evolutionary studies (2024)Reproducible and replicable pain research: a critical review (2018)The statistical significance filter leads to overoptimistic expectations of replicability (2018)The New Statistics for Better Science: Ask How Much, How Uncertain, and What Else Is Known (2019)
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References

  • 2010Conducting Meta-Analyses in R with the metafor Package20,412 cited
  • 2013Power failure: why small sample size undermines the reliability of neuroscience7,634 cited
  • 2008Why Most Discovered True Associations Are Inflated1,489 cited
  • 2014Beyond Power Calculations1,341 cited
  • 2011Characteristics of meta-analyses and their component studies in the Cochrane Database of Systematic Reviews: a cross-sectional, descriptive analysis403 cited
  • 2017Low statistical power in biomedical science: a review of three human research domains206 cited
  • 2021Assessing treatment effects and publication bias across different specialties in medicine: a meta-epidemiological study41 cited
  • 2021The statistical properties of RCTs and a proposal for shrinkage33 cited
  • 2022How large should the next study be? Predictive power and sample size requirements for replication studies26 cited
  • 2021Addressing Exaggeration of Effects from Single RCTs21 cited

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