STRengthening Analytical Thinking for Observational Studies: the STRATOS initiative

Authors

  • Willi Sauerbrei,

    Corresponding author
    1. Center for Medical Biometry and Medical Informatics, Medical Center – University of Freiburg
    • Correspondence to: Willi Sauerbrei, Center for Medical Biometry and Medical Informatics, Medical Center – University of Freiburg

      E-mail: wfs@imbi.uni-freiburg.de

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  • Michal Abrahamowicz,

    1. Department of Epidemiology and Biostatistics, McGill University, Montréal, QC H3A 0G4, Canada
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  • Douglas G. Altman,

    1. Centre for Statistics in Medicine, University of Oxford, Oxford OX3 7LD [Correction added on 15 August 2014, after first online publication: Postcode OX1 2JD has been corrected to OX3 7LD], U.K.
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  • Saskia le Cessie,

    1. Department of Clinical Epidemiology and Department for Medical Statistics and Bioinformatics, Leiden University Medical Centre, 2333 ZA Leiden, The Netherlands
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  • James Carpenter,

    1. Medical Statistics Unit, London School of Hygiene and Tropical Medicine, and MRC Clinical Trials Unit, Kingsway, London, U.K.
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  • on behalf of the STRATOS initiative


  • Correction added on 15 August 2014, after first online publication: placement of ’and’ corrected.

Abstract

The validity and practical utility of observational medical research depends critically on good study design, excellent data quality, appropriate statistical methods and accurate interpretation of results. Statistical methodology has seen substantial development in recent times. Unfortunately, many of these methodological developments are ignored in practice. Consequently, design and analysis of observational studies often exhibit serious weaknesses. The lack of guidance on vital practical issues discourages many applied researchers from using more sophisticated and possibly more appropriate methods when analyzing observational studies. Furthermore, many analyses are conducted by researchers with a relatively weak statistical background and limited experience in using statistical methodology and software. Consequently, even ‘standard’ analyses reported in the medical literature are often flawed, casting doubt on their results and conclusions. An efficient way to help researchers to keep up with recent methodological developments is to develop guidance documents that are spread to the research community at large.

These observations led to the initiation of the strengthening analytical thinking for observational studies (STRATOS) initiative, a large collaboration of experts in many different areas of biostatistical research. The objective of STRATOS is to provide accessible and accurate guidance in the design and analysis of observational studies. The guidance is intended for applied statisticians and other data analysts with varying levels of statistical education, experience and interests.

In this article, we introduce the STRATOS initiative and its main aims, present the need for guidance documents and outline the planned approach and progress so far. We encourage other biostatisticians to become involved. © 2014 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd.

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