Causal Inference: Efficacy and Mechanism Evaluation

Sabine Landau; Richard Emsley

doi:10.1007/978-3-319-52636-2_137

Causal Inference: Efficacy and Mechanism Evaluation

Sabine Landau^*, Richard Emsley

^*Corresponding author for this work

King's College London

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

In randomized trials, the primary analysis is usually based on an intention-to-treat approach which answers the question “What is the effect of offering treatment?” There are many other questions that investigators could pose such as “Does this treatment work if it is received?” “What factors make the treatment work better?” and “How does the treatment work?” These questions require alternative analysis approaches based on statistical methods drawn from the causal inference literature, including instrumental variables and causal mediation analysis. This chapter will define relevant causal estimands and describe methods that can be used to estimate them, their underlying assumptions, and the estimation procedures. The methods will be illustrated using examples drawn from the literature.

Original language	English
Title of host publication	Principles and Practice of Clinical Trials
Publisher	Springer International Publishing
Pages	1981-2002
Number of pages	22
ISBN (Electronic)	9783319526362
ISBN (Print)	9783319526355
DOIs	https://doi.org/10.1007/978-3-319-52636-2_137
Publication status	Published - 1 Jan 2022

Keywords

Confounding
Controlled direct effect
Efficacy
Estimand
Instrumental variables methods
Mechanism
Mediation analysis
Nonadherence
Process variable
Treatment effect modification

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KW - Mechanism

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KW - Process variable

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Causal Inference: Efficacy and Mechanism Evaluation

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