Missing Data Review

Missing Data Review is a systematic methodological process within data analysis that identifies, assesses, and addresses the patterns and implications of absent or incomplete data entries in a dataset to ensure the validity and reliability of empirical findings.

27

Publications

1.9K

Citations

81

Authors

62

Institutions

Publications per year

2017–2026

11

Authors

81

  1. BV
    Ben Van Dusen

    California State University, Chico, United States

    2 publications · 74 citations

    2

    h-index

  2. SE
    Shanil Ebrahim

    McMaster University, Canada

    2 publications · 187 citations

    2

    h-index

  3. HJ
    Holger J. Schünemann

    McMaster University, Canada

    2 publications · 54 citations

    2

    h-index

  4. TD
    Todd D. Little

    University of Kansas, United States

    2 publications · 357 citations

    2

    h-index

  5. LM
    Loukia M. Spineli

    Medizinische Hochschule Hannover, Germany

    2 publications · 33 citations

    2

    h-index

1–5 of 81

Venues

  1. Journal of Clinical Epidemiology

    2 publications · 83 citations

    2

    h-index

  2. PubMed

    Repository · 2 publications · 155 citations

    2

    h-index

  3. Gaceta Sanitaria

    1 publications · 28 citations

    1

    h-index

  4. Policing An International Journal

    PIJPSM · 1 publications · 13 citations

    1

    h-index

  5. International Journal of Behavioral Development

    IJBD · 1 publications · 65 citations

    1

    h-index

1–5