Salīdzināt metodes

	Meta-regresijas metaanalīze	Bibliometriskā analīze
Nozare	Zinātnometrija	Zinātnometrija
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1993–1999	1969 (term coined); practice dates to 1920s–1930s
Autors	Stephen G. Thompson & Simon J. Sharp (systematic framework); earlier work by Berlin, Longnecker & Greenland (1993)	Alan Pritchard (coined term); earlier quantitative work by Paul Otlet (1934) and S. C. Bradford (1934)
Tips	Quantitative evidence synthesis with covariate modeling	Quantitative literature analysis
Pirmavots	Thompson, S. G., & Sharp, S. J. (1999). Explaining heterogeneity in meta-analysis: a comparison of methods. Statistics in Medicine, 18(20), 2693–2708.	Pritchard, A. (1969). Statistical bibliography or bibliometrics? Journal of Documentation, 25(4), 348–349.
Citi nosaukumi	meta-regression, meta-analytic regression, weighted regression meta-analysis, MR-MA	bibliometrics, bibliometric study, bibliometric mapping, publication analysis
Saistītās	4	6
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.	Bibliometric analysis applies statistical and mathematical methods to bibliographic records — publications, citations, authors, journals, and keywords — to measure and map the structure, output, and intellectual evolution of a research field. It is widely used to identify influential works, prolific authors, productive journals, collaboration networks, and emerging research themes across any academic discipline.