เปรียบเทียบวิธี

	การวิเคราะห์อภิมานแบบอิงการถดถอยอภิมาน	การทบทวนวรรณกรรมอย่างเป็นระบบ (Systematic Literature Review
สาขาวิชา	วิทยาศาสตรมิติ	วิทยาศาสตรมิติ
ตระกูล	Process / pipeline	Process / pipeline
ปีกำเนิด	1993–1999	1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines)
ผู้ริเริ่ม	Stephen G. Thompson & Simon J. Sharp (systematic framework); earlier work by Berlin, Longnecker & Greenland (1993)	Archie Cochrane (conceptual foundation); formalized by the Cochrane Collaboration (1993) and Barbara Kitchenham in software engineering (2004)
ประเภท	Quantitative evidence synthesis with covariate modeling	Evidence synthesis methodology
แหล่งต้นตำรับ	Thompson, S. G., & Sharp, S. J. (1999). Explaining heterogeneity in meta-analysis: a comparison of methods. Statistics in Medicine, 18(20), 2693–2708.	Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Keele University Technical Report TR/SE-0401.
ชื่อเรียกอื่น	meta-regression, meta-analytic regression, weighted regression meta-analysis, MR-MA	SLR, systematic review, evidence synthesis review, structured literature review
ที่เกี่ยวข้อง	4	5
สรุป	Meta-regression-based meta-analysis extends standard meta-analysis by fitting a weighted regression model in which study-level characteristics (moderators) predict observed effect sizes. Rather than simply pooling effects, this approach asks why effects vary across studies — linking heterogeneity in outcomes to differences in population, intervention, design, or measurement features. It is the primary tool for explaining between-study variance in quantitative evidence synthesis.	A systematic literature review (SLR) is a structured, reproducible method for identifying, appraising, and synthesizing all relevant studies on a research question. Unlike a narrative review, it follows an explicit, pre-specified protocol — from database search strings through inclusion criteria to data extraction — so that the process is transparent, auditable, and replicable by other researchers. It is widely used in medicine, education, software engineering, and the social sciences to produce the most comprehensive possible evidence base on a topic.