Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Mínimos Cuadrados Generalizados (GLS)× | Meta-análisis en Red× | |
|---|---|---|
| Campo≠ | Estadística | Síntesis de evidencia |
| Familia≠ | Regression model | Process / pipeline |
| Año de origen≠ | 1935 | 2002 |
| Autor original≠ | Alexander Craig Aitken | Lumley (2002) |
| Tipo≠ | Linear estimator | Method |
| Fuente seminal≠ | Aitken, A. C. (1935). IV.—On least squares and linear combination of observations. Proceedings of the Royal Society of Edinburgh, 55, 42–48. DOI ↗ | Lumley, T. (2002). Network meta-analysis for indirect treatment comparisons. Statistics in Medicine, 21(16), 2313–2324. DOI ↗ |
| Alias≠ | GLS, Aitken estimator, EGLS, feasible GLS | Mixed Treatment Comparison, MTC, Indirect Comparison Meta-Analysis |
| Relacionados≠ | 3 | 1 |
| Resumen≠ | Generalized Least Squares (GLS) is a linear regression estimator that extends ordinary least squares to handle situations where the error terms are correlated or have non-constant variance (heteroscedasticity). Introduced by Alexander Craig Aitken in 1935, GLS achieves the Best Linear Unbiased Estimator (BLUE) under a general error covariance structure by weighting observations according to their precision, providing a theoretical bridge between OLS and modern linear mixed models. | 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. |
| ScholarGateConjunto de datos ↗ |
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