方法对比
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| 摘要写作：撰写有效的学术摘要× | 统计报告标准：分析的透明报告× | |
|---|---|---|
| 领域 | 学术写作 | 学术写作 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1950 | 2005 |
| 提出者≠ | Scientific publishing community; formalized by ICMJE and indexing services (MEDLINE, Web of Science) | Statistical and methodological literature; emphasized by Cumming (2013), ICMJE, and replication crisis discussions |
| 类型 | Guideline | Guideline |
| 开创性文献≠ | International Committee of Medical Journal Editors (2023). Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly Work in Medical Journals. link ↗ | Cumming, G. (2013). The new statistics: Why and how. Psychological Science, 25(1), 7–29. DOI ↗ |
| 别名 | abstract, structured abstract, unstructured abstract | reporting statistics, statistical transparency, effect size reporting |
| 相关 | 4 | 4 |
| 摘要≠ | An abstract is a self-contained, concise summary of a research article that enables readers to quickly understand the study's purpose, methods, results, and conclusions without reading the full paper. Abstracts are the primary gateway to published literature: they appear in journal issues, bibliographic databases (MEDLINE, Web of Science, Scopus), and search engine results. Well-written abstracts increase citation rates and visibility; poorly written ones obscure important research. The ICMJE and major journals mandate abstracts for original research, with structured formats (Background, Methods, Results, Conclusions) becoming increasingly standard. | Transparent reporting of statistical results—including effect sizes, confidence intervals, p-values, and assumptions—is essential for scientific integrity and reproducibility. Many published studies report p-values in isolation without effect sizes or confidence intervals, making it impossible for readers to assess the magnitude of findings. Statistical reporting standards, emphasized by Cumming (2013), the American Statistical Association, and the ICMJE, require effect sizes, confidence intervals, and discussion of uncertainty. This enables readers to judge whether findings are practically significant (not just statistically significant) and to compare effect sizes across studies in meta-analyses. Poor statistical reporting wastes research and prevents proper synthesis of evidence. |
| ScholarGate数据集 ↗ |
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