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Anàlisi meta-analítica de la relació dosi-resposta×Mínims Quadrats Generalitzats (GLS)×
CampEpidemiologiaEstadística
FamíliaProcess / pipelineRegression model
Any d'origen19921935
Autor originalSander Greenland & Matthew P. LongneckerAlexander Craig Aitken
TipusQuantitative meta-analytic methodLinear estimator
Font seminalGreenland, S., & Longnecker, M. P. (1992). Methods for trend estimation from summarized dose-response data, with applications to meta-analysis. American Journal of Epidemiology, 135(11), 1301–1309. DOI ↗Aitken, A. C. (1935). IV.—On least squares and linear combination of observations. Proceedings of the Royal Society of Edinburgh, 55, 42–48. DOI ↗
Àliesdose-response meta-analysis, DRMA, pooled dose-response modeling, trend meta-analysisGLS, Aitken estimator, EGLS, feasible GLS
Relacionats23
ResumMeta-analytic dose-response analysis pools summary statistics from multiple epidemiological studies to characterize how disease risk changes across ordered levels of an exposure. Rather than comparing a single high-exposure group against a reference, it reconstructs a continuous or categorical exposure-risk curve across the full range of doses, providing far richer evidence about the shape and magnitude of an association than any single study can supply.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.
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ScholarGateCompara mètodes: Meta-analytic dose-response analysis · Generalized Least Squares. Recuperat el 2026-06-18 de https://scholargate.app/ca/compare