Measurement error correction and sensitivity analysis in longitudinal dietary intervention studies using an external validation study

Juned Siddique, Michael J. Daniels, Raymond J. Carroll, Trivellore E. Raghunathan, Elizabeth Stuart, Laurence S. Freedman

Research output: Contribution to journalArticle

Abstract

In lifestyle intervention trials, where the goal is to change a participant's weight or modify their eating behavior, self-reported diet is a longitudinal outcome variable that is subject to measurement error. We propose a statistical framework for correcting for measurement error in longitudinal self-reported dietary data by combining intervention data with auxiliary data from an external biomarker validation study where both self-reported and recovery biomarkers of dietary intake are available. In this setting, dietary intake measured without error in the intervention trial is missing data and multiple imputation is used to fill in the missing measurements. Since most validation studies are cross-sectional, they do not contain information on whether the nature of the measurement error changes over time or differs between treatment and control groups. We use sensitivity analyses to address the influence of these unverifiable assumptions involving the measurement error process and how they affect inferences regarding the effect of treatment. We apply our methods to self-reported sodium intake from the PREMIER study, a multi-component lifestyle intervention trial.

Original languageEnglish (US)
JournalBiometrics
DOIs
StatePublished - Jan 1 2019

Keywords

  • 24-hour dietary recall
  • Multiple imputation
  • recovery biomarker
  • sodium intake

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

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