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

American Journal of Epidemiology · 15 April 2016

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Summary

Describes a framework for analysing observational data by first specifying the protocol of the randomized trial one would ideally run, then emulating it as closely as possible. The approach helps avoid common design errors such as immortal time bias and has become a foundational method for causal analyses of routinely collected health data.

Summary written by Sterling IMRES editors. Read the original abstract at the publisher.

Authors

Cite this work

Hernán MA, Robins JM. Using Big Data to Emulate a Target Trial When a Randomized Trial Is Not Available. American Journal of Epidemiology. 2016;183(8):758-764. doi:10.1093/aje/kwv254

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