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Everything Matters: The ReproNim Perspective on Reproducible Neuroimaging
11 references·6 citing·41 second hop
Everything Matters: The ReproNim Perspective on Reproducible Neuroimaging (2019)Everything Matters: The ReproNim Perspect…What does research reproducibility mean? (2016)What does research reproducib…Reproducibility of neuroimaging analyses across operating systems (2015)Reproducibility of neuroimagi…Power failure: why small sample size undermines the reliability of neuroscience (2013)Power failure: why small samp…P-curve: A key to the file-drawer. (2013)P-curve: A key to the file-dr…Reproducible Research in Computational Science (2011)Reproducible Research in Comp…Nipype: A Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in Python (2011)Nipype: A Flexible, Lightweig…Excess Significance Bias in the Literature on Brain Volume Abnormalities (2011)Excess Significance Bias in t…Replicability is not Reproducibility:Nor is it Good Science (2009)Replicability is not Reproduc…Why Most Published Research Findings Are False (2005)Why Most Published Research F…Why Most Published Research Findings Are False (2005)Why Most Published Research F…The LONI Pipeline Processing Environment (2003)The LONI Pipeline Processing …Reporting of Artificial Intelligence Diagnostic Accuracy Studies in Pathology Abstracts: Compliance with STARD for Abstracts Guidelines (2022)Reporting of Artificial Intel…Neuroimaging-ITM: A Text Mining Pipeline Combining Deep Adversarial Learning with Interaction Based Topic Modeling for Enabling the FAIR Neuroimaging Study (2022)Neuroimaging-ITM: A Text Mini…FAIRly big: A framework for computationally reproducible processing of large-scale data (2022)FAIRly big: A framework for c…Brainhack: Developing a culture of open, inclusive, community-driven neuroscience (2021)Brainhack: Developing a cultu…File-based localization of numerical perturbations in data analysis pipelines (2020)File-based localization of nu…Emerging Opportunities for Advancing Cognitive Neuroscience (2019)Emerging Opportunities for Ad…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)Estimating the reproducibility of psychological science (2015)Meta-analysis and the science of research synthesis (2018)Sample Size Justification (2022)Child Maltreatment and Neural Systems Underlying Emotion Regulation (2015)How open science helps researchers succeed (2016)Beyond the 30-Million-Word Gap: Children’s Conversational Exposure Is Associated With Language-Related Brain Function (2018)Two new Later Stone Age sites from the Final Pleistocene in the Falémé Valley, eastern Senegal (2024)Improving the quality of reports of meta-analyses of randomised controlled trials: the QUOROM statement (1999)Meta-analysis of Observational Studies in Epidemiology A Proposal for Reporting (2000)The CONSORT statement: revised recommendations for improving the quality of reports of parallel-group randomised trials (2001)False-Positive Psychology (2011)The Combination of Estimates from Different Experiments (1954)Quantifying heterogeneity in a meta‐analysis (2002)Measuring inconsistency in meta-analyses (2003)Meta-analytic methods for neuroimaging data explained (2012)Evaluation of Excess Significance Bias in Animal Studies of Neurological Diseases (2013)Meta-analysis of associations between human brain volume and intelligence differences: How strong are they and what do they mean? (2015)Policy: NIH plans to enhance reproducibility (2014)The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update (2016)A solution to minimum sample size for regressions (2020)CONSORT 2025 statement: updated guideline for reporting randomised trials (2025)CONSORT 2025 statement: updated guideline for reporting randomised trials (2025)Experimental and Quasi-Experimental Designs for Research (1963)A power primer. (1992)Bias in meta-analysis detected by a simple, graphical test (1997)Scientific method: Statistical errors (2014)The Extent and Consequences of P-Hacking in Science (2015)Mini Meta‐Analysis of Your Own Studies: Some Arguments on Why and a Primer on How (2016)Increasing value and reducing waste in research design, conduct, and analysis (2014)Reproducibility in Science (2014)An introduction to Docker for reproducible research (2015)Neural Correlates of Direct and Reflected Self-Appraisals in Adolescents and Adults: When Social Perspective-Taking Informs Self-Perception (2009)Social status modulates neural activity in the mentalizing network (2012)Tools and techniques for computational reproducibility (2016)Journal of Computational Neuroscience (2013)On the scientific superiority of conceptual replications for scientific progress (2016)Scientific workflows for computational reproducibility in the life sciences: Status, challenges and opportunities (2017)The New Statistics (2013)The ethics of algorithms: Mapping the debate (2016)
this work references cited by second hop

References

  • 2005Why Most Published Research Findings Are False10,471 cited
  • 2013Power failure: why small sample size undermines the reliability of neuroscience7,634 cited
  • 2005Why Most Published Research Findings Are False4,702 cited
  • 2011Nipype: A Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in Python2,202 cited
  • 2013P-curve: A key to the file-drawer.1,501 cited
  • 2011Reproducible Research in Computational Science1,446 cited
  • 2016What does research reproducibility mean?1,291 cited
  • 2003The LONI Pipeline Processing Environment310 cited
  • 2011Excess Significance Bias in the Literature on Brain Volume Abnormalities299 cited
  • 2009Replicability is not Reproducibility:Nor is it Good Science231 cited
  • 2015Reproducibility of neuroimaging analyses across operating systems137 cited

Cited by

  • 2021Brainhack: Developing a culture of open, inclusive, community-driven neuroscience50 cited
  • 2022FAIRly big: A framework for computationally reproducible processing of large-scale data44 cited
  • 2019Emerging Opportunities for Advancing Cognitive Neuroscience14 cited
  • 2020File-based localization of numerical perturbations in data analysis pipelines

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10 cited
  • 2022Reporting of Artificial Intelligence Diagnostic Accuracy Studies in Pathology Abstracts: Compliance with STARD for Abstracts Guidelines10 cited
  • 2022Neuroimaging-ITM: A Text Mining Pipeline Combining Deep Adversarial Learning with Interaction Based Topic Modeling for Enabling the FAIR Neuroimaging Study3 cited