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| 메타회귀분석 기반 메타분석× | 네트워크 메타분석× | |
|---|---|---|
| 분야≠ | 과학계량학 | 근거 합성 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1993–1999 | 2002 |
| 창시자≠ | Stephen G. Thompson & Simon J. Sharp (systematic framework); earlier work by Berlin, Longnecker & Greenland (1993) | Lumley (2002) |
| 유형≠ | Quantitative evidence synthesis with covariate modeling | Method |
| 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 ↗ | Lumley, T. (2002). Network meta-analysis for indirect treatment comparisons. Statistics in Medicine, 21(16), 2313–2324. DOI ↗ |
| 별칭≠ | meta-regression, meta-analytic regression, weighted regression meta-analysis, MR-MA | Mixed Treatment Comparison, MTC, Indirect Comparison Meta-Analysis |
| 관련≠ | 4 | 1 |
| 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. | 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. |
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