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Estimands: improving inference in randomized controlled trials in clinical nutrition in the presence of missing values

European Journal of Clinical Nutrition volume 72, pages 1291–1295 (2018)Cite this article

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Abstract

For randomized controlled trials, the impact of the amount and handling of missing data on the interpretation of the treatment effect has been unclear. The current use of intention to treat, per protocol, and complete-case analysis has shortcomings. The use of estimands may lead to improved estimation of treatment effects through more precise characterizations of the fate of treatments after dropout or other post-randomization events. A perspective on current and future developments with a view toward clinical nutrition is provided.

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Authors and Affiliations

  1. Department of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, Copenhagen, Denmark

    Christian Ritz

  2. Biometrics, Leo Pharma a/s, Copenhagen, Denmark

    Birgitte Rønn

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  1. Christian Ritz
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  2. Birgitte Rønn
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Correspondence to Christian Ritz.

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The authors declare that they have no conflict of interest.

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Ritz, C., Rønn, B. Estimands: improving inference in randomized controlled trials in clinical nutrition in the presence of missing values. Eur J Clin Nutr 72, 1291–1295 (2018). https://doi.org/10.1038/s41430-018-0207-x

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  • DOI: https://doi.org/10.1038/s41430-018-0207-x

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