Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available

Ideally, questions about comparative effectiveness or safety would be answered using an appropriately designed and conducted randomized experiment. When we cannot conduct a randomized experiment, we analyze observational data. Causal inference from large observational databases (big data) can be vie...

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Veröffentlicht in:	American journal of epidemiology Jg. 183; H. 8; S. 758
Hauptverfasser:	Hernán, Miguel A, Robins, James M
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States 15.04.2016
Schlagworte:	Breast Neoplasms - epidemiology Breast Neoplasms - etiology Causality Comparative Effectiveness Research - methods Comparative Effectiveness Research - standards Databases, Factual - statistics & numerical data Drug Therapy, Combination Estrogen Replacement Therapy - adverse effects Estrogen Replacement Therapy - statistics & numerical data Female Humans Observational Studies as Topic - methods Observational Studies as Topic - standards Postmenopause Progestins - adverse effects Progestins - therapeutic use Propensity Score Randomized Controlled Trials as Topic - methods Randomized Controlled Trials as Topic - standards comparative effectiveness research big data causal inference target trial
ISSN:	1476-6256, 1476-6256
Online-Zugang:	Weitere Angaben
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