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The preregistration revolution needs to distinguish between predictions and analyses
9 references·5 citing·38 second hop
The preregistration revolution needs to distinguish between predictions and analyses (2018)The preregistration revolution needs to d…The preregistration revolution (2018)The preregistration revolutionWhen Does HARKing Hurt? Identifying When Different Types of Undisclosed Post Hoc Hypothesizing Harm Scientific Progress (2017)When Does HARKing Hurt? Ident…Pre-registration in social psychology—A discussion and suggested template (2016)Pre-registration in social ps…The Statistical Crisis in Science (2014)The Statistical Crisis in Sci…The meaning of “significance” for different types of research [translated and annotated by Eric-Jan Wagenmakers, Denny Borsboom, Josine Verhagen, Rogier Kievit, Marjan Bakker, Angelique Cramer, Dora Matzke, Don Mellenbergh, and Han L. J. van der Maas] (2014)The meaning of “significance”…False-Positive Psychology (2011)False-Positive PsychologyError and inference: recent exchanges on experimental reasoning, reliability, and the objectivity and rationality of science (2010)Error and inference: recent e…Novel Evidence and Severe Tests (1991)Novel Evidence and Severe Tes…CONJECTURES AND REFUTATIONS (1963)CONJECTURES AND REFUTATIONSJust a number? Using artificial intelligence to explore perceived founder age in entrepreneurial fundraising (2023)Just a number? Using artifici…Reframing the perception of outliers and negative data in translational research (2022)Reframing the perception of o…Replication in entrepreneurship (2021)Replication in entrepreneursh…What should a preregistration contain? (2020)What should a preregistration…Reply to Ledgerwood: Predictions without analysis plans are inert (2018)Reply to Ledgerwood: Predicti…Why Most Published Research Findings Are False (2005)Why Most Published Research Findings Are False (2005)Degrees of Freedom in Planning, Running, Analyzing, and Reporting Psychological Studies: A Checklist to Avoid p-Hacking (2016)A manifesto for reproducible science (2017)Objective Knowledge, an Evolutionary Approach. (1973)OBJECTIVE KNOWLEDGE: AN EVOLUTIONARY APPROACH (1973)Prediction Versus Accommodation and the Risk of Overfitting (2004)Statistical Inference as Severe Testing (2018)The case for motivated reasoning. (1990)Measuring the Prevalence of Questionable Research Practices With Incentives for Truth Telling (2012)Scientific Utopia (2012)Power failure: why small sample size undermines the reliability of neuroscience (2013)The Ancestral Logic of Politics (2013)oTree - An Open-Source Platform for Laboratory, Online, and Field Experiments (2016)Scientists rise up against statistical significance (2019)Publication bias in clinical research (1991)The New Statistics (2013)The association between adolescent well-being and digital technology use (2019)Teenagers, screens and social media: a narrative review of reviews and key studies (2020)Falsification and the Methodology of Scientific Research Programmes (1970)Estimating the reproducibility of psychological science (2015)Systematic reviews and meta-analyses in the health sciences: Best practice methods for research syntheses (2019)Beyond intrinsic and extrinsic motivation: A meta-analysis on self-determination theory’s multidimensional conceptualization of work motivation (2021)Reducing bias, increasing transparency and calibrating confidence with preregistration (2023)Judgment under Uncertainty: Heuristics and Biases (1975)Thinking, Fast and Slow (2011)Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015 (2018)Many Labs 2: Investigating Variation in Replicability Across Samples and Settings (2018)Replicability, Robustness, and Reproducibility in Psychological Science (2021)Upper Echelons: The Organization as a Reflection of Its Top Managers (1984)A model of (often mixed) stereotype content: Competence and warmth respectively follow from perceived status and competition. (2002)Role congruity theory of prejudice toward female leaders. (2002)Entrepreneurship and artificial intelligence: a bibliometric analysis (2024)Old but gold? Examining the effect of age bias in reward-based crowdfunding (2024)A Review of Artificial Intelligence, Algorithms, and Robots Through the Lens of Stakeholder Theory (2025)Falsification and the Methodology of Scientific Research Programmes (1976)Conjectures and Refutations (2020)A Confrontation of Convergent Realism (2013)
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References

  • 2011False-Positive Psychology6,587 cited
  • 1963CONJECTURES AND REFUTATIONS2,858 cited
  • 2018The preregistration revolution2,252 cited
  • 2014The Statistical Crisis in Science1,010 cited
  • 2016Pre-registration in social psychology—A discussion and suggested template464 cited
  • 2014The meaning of “significance” for different types of research [translated and annotated by Eric-Jan Wagenmakers, Denny Borsboom, Josine Verhagen, Rogier Kievit, Marjan Bakker, Angelique Cramer, Dora Matzke, Don Mellenbergh, and Han L. J. van der Maas]190 cited
  • 2017When Does HARKing Hurt? Identifying When Different Types of Undisclosed Post Hoc Hypothesizing Harm Scientific Progress181 cited
  • 1991Novel Evidence and Severe Tests152 cited
  • 2010Error and inference: recent exchanges on experimental reasoning, reliability, and the objectivity and rationality of science140 cited

Cited by

  • 2023Just a number? Using artificial intelligence to explore perceived founder age in entrepreneurial fundraising37 cited
  • 2021Replication in entrepreneurship23 cited
  • 2020What should a preregistration contain?16 cited
  • 2018Reply to Ledgerwood: Predictions without analysis plans are inert8 cited
  • 2022Reframing the perception of outliers and negative data in translational research

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5 cited