Bandingkan kaedah

	Rangkaian EQUATOR: Piawaian Pelaporan Penyelidikan Kesihatan	Piawaian Pelaporan Statistik: Pelaporan Analisis yang Telusur
Bidang	Penulisan Akademik	Penulisan Akademik
Keluarga	Process / pipeline	Process / pipeline
Tahun asal	2006	2005
Pengasas	EQUATOR Network (founded 2006); hosted by University of Oxford	Statistical and methodological literature; emphasized by Cumming (2013), ICMJE, and replication crisis discussions
Jenis	Standard	Guideline
Sumber perintis	Moher, D., Altman, D. G., Schulz, K. F., Simera, I., & Wager, E. (2012). Guidelines for reporting health research: A user's manual. British Medical Journal, 345, e5997.	Cumming, G. (2013). The new statistics: Why and how. Psychological Science, 25(1), 7–29.
Alias	EQUATOR, reporting guidelines, PRISMA, CONSORT	reporting statistics, statistical transparency, effect size reporting
Berkaitan	4	4
Ringkasan	EQUATOR (Enhancing QUAlity and Transparency Of health Research) is a global network that develops, endorses, and promotes reporting guidelines for health and life sciences research. Founded in 2006 and hosted by the University of Oxford, EQUATOR maintains a library of 500+ guidelines covering study designs (randomized trials, observational studies, systematic reviews, case reports, qualitative research, etc.). Major guidelines include CONSORT (randomized controlled trials), STROBE (observational studies), PRISMA (systematic reviews and meta-analyses), and CARE (case reports). These guidelines specify which items must be reported and how to report them, reducing inconsistency and enabling readers to assess study validity. Many journals now require adherence to relevant EQUATOR guidelines.	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.