Salīdzināt metodes

	Meta-regresijas metaanalīze	Meta-analīze tīklā
Nozare	Zinātnometrija	Pierādījumu sintēze
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1993–1999	2002
Autors	Stephen G. Thompson & Simon J. Sharp (systematic framework); earlier work by Berlin, Longnecker & Greenland (1993)	Lumley (2002)
Tips	Quantitative evidence synthesis with covariate modeling	Method
Pirmavots	Thompson, S. G., & Sharp, S. J. (1999). Explaining heterogeneity in meta-analysis: a comparison of methods. Statistics in Medicine, 18(20), 2693–2708.	Lumley, T. (2002). Network meta-analysis for indirect treatment comparisons. Statistics in Medicine, 21(16), 2313–2324.
Citi nosaukumi	meta-regression, meta-analytic regression, weighted regression meta-analysis, MR-MA	Mixed Treatment Comparison, MTC, Indirect Comparison Meta-Analysis
Saistītās	4	1
Kopsavilkums	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.	Network meta-analysis (NMA) is a systematic method for comparing multiple interventions simultaneously within a single analytical framework, incorporating both direct evidence (head-to-head trials) and indirect evidence (comparisons via common comparators). First formalized by Lumley in 2002, NMA allows researchers to rank treatments and quantify comparative effectiveness even when some treatment pairs have never been directly studied.