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The multiplicity of analysis strategies jeopardizes replicability: lessons learned across disciplines
16 references·1 citing·37 second hop
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References

  • 2005Why Most Published Research Findings Are False10,471 cited
  • 2015Estimating the reproducibility of psychological science8,516 cited
  • 2013Power failure: why small sample size undermines the reliability of neuroscience7,634 cited
  • 1989Design and Analysis of Computer Experiments6,958 cited
  • 2011Specification, evaluation, and interpretation of structural equation models3,734 cited
  • 2019Scientists rise up against statistical significance2,997 cited
  • 2015Promoting an open research culture2,686 cited
  • 2013At what sample size do correlations stabilize?2,229 cited
  • 2017Choosing Prediction Over Explanation in Psychology: Lessons From Machine Learning1,928 cited
  • 2011Believe it or not: how much can we rely on published data on potential drug targets?1,885 cited
  • 2008Why Most Discovered True Associations Are Inflated1,489 cited
  • 2016What does research reproducibility mean?1,291 cited
  • 2004Probabilistic Sensitivity Analysis of Complex Models: A Bayesian Approach1,085 cited
  • 2017Inoculating the Public against Misinformation about Climate Change1,058 cited
  • 2012An Agenda for Purely Confirmatory Research1,041 cited

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  • 2014The Statistical Crisis in Science959 cited
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    • 2021Statisticians, Roll Up Your Sleeves! There's A Crisis to be Solved7 cited