So sánh phương pháp

	Phản hồi các nhận xét của người phản biện: Thư sửa đổi và Bản thảo sửa đổi	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	2005	2005
Người khởi xướng	Journal editors and publishing community; formalized by Clydesdale et al. and ICMJE	Statistical and methodological literature; emphasized by Cumming (2013), ICMJE, and replication crisis discussions
Loại	Guideline	Guideline
Công trình gốc	Clydesdale, G. J., Seymour, K. J., & Toy, M. S. (2013). How to write a response to reviewers. British Journal of Ophthalmology, 97(1), 1–2.	Cumming, G. (2013). The new statistics: Why and how. Psychological Science, 25(1), 7–29.
Tên gọi khác	revision letter, response to reviewers, rebuttal letter	reporting statistics, statistical transparency, effect size reporting
Liên quan	4	4
Tóm tắt	A response to reviewers (or 'revision letter') is a formal document that authors submit alongside a revised manuscript, addressing each reviewer comment point-by-point. The response letter shows the editor and reviewers that you have carefully considered their feedback, explained changes made in light of their suggestions, and justified any points of disagreement. A thoughtful, respectful response to reviewers significantly increases the likelihood of acceptance; a dismissive or defensive response can lead to rejection despite good science. The response letter is not an argument but a demonstration of engagement, transparency, and scientific integrity.	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.