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| 메타회귀분석 기반 메타분석× | 계량서지 분석× | |
|---|---|---|
| 분야 | 과학계량학 | 과학계량학 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1993–1999 | 1969 (term coined); practice dates to 1920s–1930s |
| 창시자≠ | 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) |
| 유형≠ | Quantitative evidence synthesis with covariate modeling | Quantitative literature analysis |
| 원전≠ | Thompson, S. G., & Sharp, S. J. (1999). Explaining heterogeneity in meta-analysis: a comparison of methods. Statistics in Medicine, 18(20), 2693–2708. DOI ↗ | Pritchard, A. (1969). Statistical bibliography or bibliometrics? Journal of Documentation, 25(4), 348–349. link ↗ |
| 별칭 | meta-regression, meta-analytic regression, weighted regression meta-analysis, MR-MA | bibliometrics, bibliometric study, bibliometric mapping, publication analysis |
| 관련≠ | 4 | 6 |
| 요약≠ | 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. |
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