Examples of Applying Causal-Inference Roadmap to Real-World Studies

Yixin Fang ()
Additional contact information
Yixin Fang: AbbVie, Data and Statistical Sciences

A chapter in Real-World Evidence in Medical Product Development, 2023, pp 341-364 from Springer

Abstract: Abstract The causal-inference roadmap described in Chapter 8 consists of six key steps to derive real-world evidence (RWE) from the analysis of real-world data (RWD) generated from real-world studies. In this chapter, we demonstrate the application of the roadmap through examples. These examples are generated using a subset of the NHEFS (National Health and Nutrition Examination Survey Data I Epidemiologic Follow-up Study), combined with simulated outcomes, missing data, and intercurrent events. This demonstration shows that the causal-inference roadmap is useful in analyzing real-world data with confounders, missing data, and intercurrent events.

Keywords: Causal inference; Real-world data; Real-world evidence; R software; Sensitivity analysis; Targeted learning (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-26328-6_18

Ordering information: This item can be ordered from
http://www.springer.com/9783031263286

DOI: 10.1007/978-3-031-26328-6_18

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().