Misreporting Detection

Misreporting Detection is a methodological construct within dietary assessment that identifies systematic inaccuracies in self-reported nutrient intake data by distinguishing between plausible and implausible reporting behaviors based on physiological and statistical benchmarks.

56

Publications

4.3K

Citations

311

Authors

190

Institutions

Publications per year

2017–2026

19

Authors

311

  1. AF
    Amy F. Subar

    National Cancer Institute, United States

    3 publications · 323 citations

    3

    h-index

  2. DJ
    Daniël J. Hoffman

    Rutgers, The State University of New Jersey, United States

    2 publications · 114 citations

    2

    h-index

  3. MA
    Megan A. McCrory

    Tufts University, United States

    2 publications · 519 citations

    2

    h-index

  4. KH
    Kirsi H. Pietiläinen

    University of Helsinki, Finland

    2 publications · 133 citations

    2

    h-index

  5. SW
    Stephen Whybrow

    University of Aberdeen, United Kingdom

    2 publications · 144 citations

    2

    h-index

1–5 of 311

Venues

  1. European Journal of Clinical Nutrition

    EJCN · 8 publications · 715 citations

    8

    h-index

  2. International Journal of Obesity

    3 publications · 603 citations

    3

    h-index

  3. British Journal Of Nutrition

    BJN · 3 publications · 243 citations

    3

    h-index

  4. The Journal of Human Resources

    JHR · 2 publications · 40 citations

    2

    h-index

  5. PubMed

    Repository · 2 publications · 145 citations

    2

    h-index

1–5