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What’s new in the quantification of causal effects from longitudinal cohort studies: a brief introduction to marginal structural models for intensivists

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Authors and Affiliations

  1. U823, Grenoble Alpes University, Rond-point de la Chantourne, 38700, La Tronche, France

    S. Bailly

  2. UMR 1137, IAME Team 5, DeSCID: Decision SCiences in Infectious Diseases, Control and Care Inserm/Paris Diderot, Sorbonne Paris Cité University, 16 rue Henri Huchard, 75018, Paris, France

    S. Bailly & J. F. Timsit

  3. Department of Anesthesia and Perioperative Care, San Francisco General Hospital and Trauma Center, University of California San Francisco, San Francisco, CA, USA

    R. Pirracchio

  4. Division of Biostatistics, School of Public Health, University of California at Berkeley, Berkeley, CA, USA

    R. Pirracchio

  5. Medical and Infectious Diseases ICU-Paris Diderot University/Bichat Hospital, 46 rue Henri Huchard, 75018, Paris, France

    J. F. Timsit

Authors
  1. S. Bailly
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  2. R. Pirracchio
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  3. J. F. Timsit
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Correspondence to S. Bailly.

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Bailly, S., Pirracchio, R. & Timsit, J.F. What’s new in the quantification of causal effects from longitudinal cohort studies: a brief introduction to marginal structural models for intensivists. Intensive Care Med 42, 576–579 (2016). https://doi.org/10.1007/s00134-015-3919-6

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  • DOI: https://doi.org/10.1007/s00134-015-3919-6

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