ArticleProceedings of the National Academy of Sciences of the United States of America2018
Issues with data and analyses: Errors, underlying themes, and potential solutions.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
59 citing papers in PubMed.
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- No compelling evidence of sex differences in brain maturation during COVID-19 lockdowns when the sexes are compared statistically.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Integrated data-driven biotechnology research environments.Database : the journal of biological databases and curation · 2025Review
- An Overview of Reviews on the Association of Low Calorie Sweetener Consumption With Body Weight and Adiposity.Advances in nutrition (Bethesda, Md.) · 2024Review
- Verification of nucleotide sequence reagent identities in original publications in high impact factor cancer research journals.Naunyn-Schmiedeberg's archives of pharmacology · 2024Article
- Accelerating Resident Research within Quantitative Collaboration Units in Academic Healthcare.Stat (International Statistical Institute) · 2024Article
- Facilitators for and Barriers to the Implementation of Performance Accountability Mechanisms for Quality Improvement in the Delivery of Maternal Health Services in a District Hospital in Pwani Region, Tanzania.International journal of environmental research and public health · 2023Article
- Teaching students to R3eason, not merely to solve problem sets: The role of philosophy and visual data communication in accessible data science education.PLoS computational biology · 2023Article
- BatMan: Mitigating Batch Effects Via Stratification for Survival Outcome Prediction.JCO clinical cancer informatics · 2023Article
- Replication and Reproducibility and the Self-Correction of Science: What CanJID innovations : skin science from molecules to population health · 2023Article
- Reanalysis Accounting for Clustering and Nesting Overturns Conclusions in: "Watching TV Cooking Programs: Effects on Actual Food Intake Among Children".Journal of nutrition education and behavior · 2023Article
- Thirty-three myths and misconceptions about population data: from data capture and processing to linkage.International journal of population data science · 2023Article
- Editorial: New technologies and statistical models applied to sports and exercise science research: methodological, technical and practical considerations.Frontiers in sports and active living · 2023Article
- Social determinants of health derived from people with opioid use disorder: Improving data collection, integration and use with cross-domain collaboration and reproducible, data-centric, notebook-style workflows.Frontiers in medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Some aspects of science, taken at the broadest level, are universal in empirical research. These include collecting, analyzing, and reporting data. In each of these aspects, errors can and do occur. In this work, we first discuss the importance of focusing on statistical and data errors to continually improve the practice of science. We then describe underlying themes of the types of errors and postulate contributing factors. To do so, we describe a case series of relatively severe data and statistical errors coupled with surveys of some types of errors to better characterize the magnitude, frequency, and trends. Having examined these errors, we then discuss the consequences of specific errors or classes of errors. Finally, given the extracted themes, we discuss methodological, cultural, and system-level approaches to reducing the frequency of commonly observed errors. These approaches will plausibly contribute to the self-critical, self-correcting, ever-evolving practice of science, and ultimately to furthering knowledge.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.