Võrdle meetodeid
Vaata valitud meetodeid kõrvuti; erinevad read on esile tõstetud.
| Võrkelementanalüüs× | Meta-regressioon× | |
|---|---|---|
| Valdkond≠ | Tõendite süntees | Metaanalüüs |
| Perekond≠ | Process / pipeline | Regression model |
| Tekkeaasta | 2002 | 2002 |
| Looja≠ | Lumley (2002) | Simon Thompson & Julian Higgins |
| Tüüp≠ | Method | Weighted regression for effect-size heterogeneity |
| Algallikas≠ | Lumley, T. (2002). Network meta-analysis for indirect treatment comparisons. Statistics in Medicine, 21(16), 2313–2324. DOI ↗ | Thompson, S. G., & Higgins, J. P. T. (2002). How should meta-regression analyses be undertaken and interpreted? Statistics in Medicine, 21(11), 1559–1573. DOI ↗ |
| Rööpnimetused≠ | Mixed Treatment Comparison, MTC, Indirect Comparison Meta-Analysis | Meta-Analytic Regression, Weighted Regression in Meta-Analysis, Moderator Analysis, Meta-regresyon |
| Seotud≠ | 1 | 2 |
| Kokkuvõte≠ | 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. | Meta-regression is a statistical technique that extends conventional meta-analysis by regressing study-level effect sizes on one or more study characteristics (moderators) to explain between-study heterogeneity. Formalized by Thompson and Higgins in 2002, it uses weighted least squares — weighting each study by the inverse of its variance — within a mixed-effects framework, allowing researchers to identify which study features systematically account for variation in observed effects across the literature. |
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