A Review of Causal Inference Methods for Estimating the Effects of Exposure Change when Incident Exposure Is Unobservable
Author:
Funder
National Cancer Institute
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s40471-024-00343-5.pdf
Reference56 articles.
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2. •• Lund JL, Richardson DB, Stürmer T. The active comparator, new user study design in pharmacoepidemiology: historical foundations and contemporary application. Curr Epidemiol Rep. 2015;2:221–8. (This paper summarized three biases that could result from not properly defining a comparison group and a treatment initiation time in pharmacoepidemiology. Among the three biases, the "heathy adherer bias" due to ill-defined treatment initiation was extended to a non-pharmacoepidemiology context in the current paper. This paper also described the "active comparator, new user" design that can mitigate the three biases, some of the principles and practices can be applied to other observational studies in non-pharmacoepidemiology.)
3. •• Brookhart MA. Counterpoint: the treatment decision design. Am J Epidemiol. 2015;182:840–5. (In a series of short papers discussing the benefits and challenges of only including participants whose first exposure were observed under study, this paper proposed an alternative approach that anchors the start of follow-up to the time when medical decisions are made instead of the first exposure. Though the paper focused on pharmacoepidemiology, the principle was extended to non-pharmacoepidemiology context in our paper.)
4. •• Hernán MA, Robins JM. Using big data to emulate a target trial when a randomized trial is not available. Am J Epidemiol. 2016;183:758–64. (This paper introduced the general framework of target trial emulation for causal analysis of observational data. Although the concept of a target trial has been around for some time, the extension to time-varying treatments expressed in this paper enables a general framework for static and dynamic treatment strategies.)
5. Hernán MA, Sauer BC, Hernández-Díaz S, Platt R, Shrier I. Specifying a target trial prevents immortal time bias and other self-inflicted injuries in observational analyses. J Clin Epidemiol. 2016;79:70–5.
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