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| 广义最小二乘法 (GLS)× | 网络荟萃分析× | |
|---|---|---|
| 领域≠ | 统计学 | 证据综合 |
| 方法族≠ | Regression model | Process / pipeline |
| 起源年份≠ | 1935 | 2002 |
| 提出者≠ | Alexander Craig Aitken | Lumley (2002) |
| 类型≠ | Linear estimator | Method |
| 开创性文献≠ | 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 ↗ |
| 别名≠ | GLS, Aitken estimator, EGLS, feasible GLS | Mixed Treatment Comparison, MTC, Indirect Comparison Meta-Analysis |
| 相关≠ | 3 | 1 |
| 摘要≠ | 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. |
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