So sánh phương pháp

	Viết Tóm tắt: Soạn thảo Tóm tắt Khoa học Hiệu quả	Tiêu chuẩn Báo cáo Thống kê: Báo cáo Minh bạch Phân tích
Lĩnh vực	Viết học thuật	Viết học thuật
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1950	2005
Người khởi xướng	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
Loại	Guideline	Guideline
Công trình gốc	International Committee of Medical Journal Editors (2023). Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly Work in Medical Journals.	Cumming, G. (2013). The new statistics: Why and how. Psychological Science, 25(1), 7–29.
Tên gọi khác	abstract, structured abstract, unstructured abstract	reporting statistics, statistical transparency, effect size reporting
Liên quan	4	4
Tóm tắt	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.