Assessing reliability in neuroimaging research through intra-class effect decomposition (ICED)

  1. Andreas M Brandmaier  Is a corresponding author
  2. Elisabeth Wenger
  3. Nils C Bodammer
  4. Simone Kühn
  5. Naftali Raz
  6. Ulman Lindenberger
  1. Max Planck Institute for Human Development, Germany
  2. University Clinic Hamburg-Eppendorf, Germany

Abstract

Magnetic resonance imaging has become an indispensable tool for studying associations between structural and functional properties of the brain and behavior in humans. However, generally recognized standards for assessing and reporting the reliability of these techniques are still lacking. Here, we introduce a new approach for assessing and reporting reliability, termed intra-class effect decomposition (ICED). ICED uses structural equation modeling of data from a repeated-measures design to decompose reliability into orthogonal sources of measurement error that are associated with different characteristics of the measurements, for example, session, day, or scanning site. This allows researchers to describe the magnitude of different error components, make inferences about error sources, and inform them in planning future studies. We apply ICED to published measurements of myelin content and resting state functional connectivity. These examples illustrate how longitudinal data can be leveraged separately or conjointly with cross-sectional data to obtain more precise estimates of reliability.

Data availability

The dataset on myelin water fraction measurements is freely available at https://osf.io/t68my/ and the link-wise resting state functional connectivity data is available at https://osf.io/8n24x/.

The following previously published data sets were used
    1. Arshad M
    2. Stanley J A
    3. Raz
    4. N
    (2018) Reliability of Myelin Water Fraction in ALIC
    Publicly available at Open Science Framework.

Article and author information

Author details

  1. Andreas M Brandmaier

    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
    For correspondence
    brandmaier@mpib-berlin.mpg.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8765-6982
  2. Elisabeth Wenger

    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
  3. Nils C Bodammer

    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
  4. Simone Kühn

    Clinic and Policlinic for Psychiatry and Psychotherapy, University Clinic Hamburg-Eppendorf, Hamburg, Germany
    Competing interests
    The authors declare that no competing interests exist.
  5. Naftali Raz

    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
  6. Ulman Lindenberger

    Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.

Funding

National Institutes of Health (R01-AG011230)

  • Naftali Raz

Horizon 2020 Framework Programme (732592)

  • Andreas M Brandmaier
  • Simone Kühn
  • Ulman Lindenberger

Max-Planck-Gesellschaft (Open-access funding)

  • Andreas M Brandmaier
  • Elisabeth Wenger
  • Nils C Bodammer
  • Naftali Raz
  • Ulman Lindenberger

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Heidi Johansen-Berg, University of Oxford, United Kingdom

Version history

  1. Received: February 6, 2018
  2. Accepted: July 1, 2018
  3. Accepted Manuscript published: July 2, 2018 (version 1)
  4. Version of Record published: July 13, 2018 (version 2)

Copyright

© 2018, Brandmaier et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Andreas M Brandmaier
  2. Elisabeth Wenger
  3. Nils C Bodammer
  4. Simone Kühn
  5. Naftali Raz
  6. Ulman Lindenberger
(2018)
Assessing reliability in neuroimaging research through intra-class effect decomposition (ICED)
eLife 7:e35718.
https://doi.org/10.7554/eLife.35718

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https://doi.org/10.7554/eLife.35718

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