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	Meta-regressionsbaserad koordsanalys	Bibliometrisk analys
Ämnesområde	Scientometri	Scientometri
Familj	Process / pipeline	Process / pipeline
Ursprungsår	2000s–2010s (hybrid application period)	1969 (term coined); practice dates to 1920s–1930s
Upphovsperson	Derived from Callon et al. (co-word analysis, 1983) and Glass (meta-regression lineage, 1976); hybrid application developed incrementally in scientometrics and evidence synthesis	Alan Pritchard (coined term); earlier quantitative work by Paul Otlet (1934) and S. C. Bradford (1934)
Typ	Hybrid scientometric-statistical method	Quantitative literature analysis
Ursprungskälla	Callon, M., Courtial, J. P., Turner, W. A., & Bauin, S. (1983). From translations to problematic networks: An introduction to co-word analysis. Social Science Information, 22(2), 191–235.	Pritchard, A. (1969). Statistical bibliography or bibliometrics? Journal of Documentation, 25(4), 348–349.
Alias	MR-CWA, meta-regression co-word mapping, regression-weighted co-word analysis, co-word meta-regression	bibliometrics, bibliometric study, bibliometric mapping, publication analysis
Närliggande	4	6
Sammanfattning	Meta-regression-based co-word analysis is a hybrid scientometric technique that enriches traditional co-word mapping by weighting keyword co-occurrence networks with meta-regression-derived effect estimates. Instead of treating all documents as equally informative, the method uses statistical regression to incorporate study-level moderators — such as publication year, sample size, or methodological quality — into the co-occurrence structure, revealing how thematic clusters in a research field vary across moderator conditions.	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.