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Assessment of assumptions of statistical analysis methods in randomised clinical trials: the what and how.

Author information

Affiliations

  • 1. Copenhagen Trial Unit, Centre for Clinical Intervention Research, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
      Authors
    • Nørskov AK 1
    (1 author)
  • 2. Department of Biostatistics, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark.
      Authors
    • Lange T 2
    (1 author)
  • 3. Copenhagen Trial Unit, Centre for Clinical Intervention Research, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
      Authors
    • Nielsen EE 3
    • Gluud C 3
    • Winkel P 3
    • Wetterslev J 3
    • Jakobsen JC 3
    (5 authors)
  • 4. Institute of Statistics, Universitat Ulm, Ulm, Baden-Württemberg, Germany.
      Authors
    • Beyersmann J 4
    (1 author)
  • 5. Department of Statistics and Operations Research & Biomedical Research Center (CINBIO), Universidade de Vigo, Vigo, Galicia, Spain.
      Authors
    • de Uña-Álvarez J 5
    (1 author)
    • Show all (9)

ORCIDs linked to this article

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BMJ Evidence-based Medicine, 27 Jan 2020, 26(3):121-126
https://doi.org/10.1136/bmjebm-2019-111268 PMID: 31988195 

Review

Abstract 

When analysing and presenting results of randomised clinical trials, trialists rarely report if or how underlying statistical assumptions were validated. To avoid data-driven biased trial results, it should be common practice to prospectively describe the assessments of underlying assumptions. In existing literature, there is no consensus on how trialists should assess and report underlying assumptions for the analyses of randomised clinical trials. With this study, we developed suggestions on how to test and validate underlying assumptions behind logistic regression, linear regression, and Cox regression when analysing results of randomised clinical trials.Two investigators compiled an initial draftbased on a review of the literature. Experienced statisticians and trialists from eight different research centres and trial units then participated in a anonymised consensus process, where we reached agreement on the suggestions presented in this paper.This paper provides detailed suggestions on 1) which underlying statistical assumptions behind logistic regression, multiple linear regression and Cox regression each should be assessed; 2) how these underlying assumptions may be assessed; and 3) what to do if these assumptions are violated.We believe that the validity of randomised clinical trial results will increase if our recommendations for assessing and dealing with violations of the underlying statistical assumptions are followed.

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Read article at publisher's site: https://doi.org/10.1136/bmjebm-2019-111268

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Funding 

Funders who supported this work.

Novo Nordisk Fonden (1)