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Causal Inference: Efficacy and Mechanism Evaluation

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Principles and Practice of Clinical Trials

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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.

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Acknowledgments

This work was supported by a grant from the UK Medical Research Council (MRC) (project Grants MR/K006185/1). R.E. was further supported by the MRC North West Hub for Trials Methodology Research (MR/K025635/1). S.L. and R.E are part-funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. S.L. is also supported by the NIHR Applied Research Collaboration South London (NIHR ARC South London) at King’s College Hospital NHS Foundation Trust. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

The work described here is the result of many years of collaborative research. The authors would like to thank Cedric Ginestet, Kim Goldsmith, Andrew Pickles, and Ian White for their contributions and suggestions. The authors dedicate this chapter to their late friend, colleague and mentor Graham Dunn, with whom these ideas were developed through many years of work.

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Authors and Affiliations

  1. Department of Biostatistics and Health Informatics, King’s College London, London, UK

    Sabine Landau & Richard Emsley

Authors
  1. Sabine Landau
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  2. Richard Emsley
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Corresponding author

Correspondence to Sabine Landau .

Editor information

Editors and Affiliations

  1. Department of Surgery, Division of Surgical Oncology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Steven Piantadosi

  2. Department of Epidemiology, School of Public Health, Johns Hopkins University, Baltimore, MD, USA

    Curtis L. Meinert

Section Editor information

  1. Department of Biostatistics and Bioinformatics, Basic Science Division, Duke University School of Medicine, Durham, NC, USA

    Stephen L. George

  2. The Johns Hopkins Center for Clinical Trials and Evidence Synthesis, Johns Hopkins University, Baltimore, MD, USA

    Curtis L. Meinert

  3. Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Steven Piantadosi

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Landau, S., Emsley, R. (2022). Causal Inference: Efficacy and Mechanism Evaluation. In: Piantadosi, S., Meinert, C.L. (eds) Principles and Practice of Clinical Trials. Springer, Cham. https://doi.org/10.1007/978-3-319-52636-2_137

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