Data Validity Checking

Data Validity Checking is a methodological procedure in epidemiologic data quality assurance that verifies the accuracy and correctness of data values by assessing their adherence to predefined semantic, syntactic, and domain-specific rules to ensure they faithfully represent the intended measured phenomena.

159

Publications

8.9K

Citations

630

Authors

332

Institutions

Publications per year

2017–2026

68

Authors

630

  1. MG
    Michael G. Kahn

    University of Colorado Denver, United States

    3 publications · 189 citations

    3

    h-index

  2. DL
    Dustin Lange

    Hasso Plattner Institute, Germany

    2 publications · 43 citations

    2

    h-index

  3. GE
    Gail E. Kaiser

    Columbia University, United States

    2 publications · 79 citations

    2

    h-index

  4. KA
    Kimberly A. Barchard

    University of Nevada, Las Vegas, United States

    2 publications · 64 citations

    2

    h-index

  5. CB
    Chris Bates

    University of Oxford, United Kingdom

    2 publications · 74 citations

    2

    h-index

1–5 of 630

Venues

  1. PubMed

    Repository · 5 publications · 102 citations

    5

    h-index

  2. 3

    h-index

  3. Sensors

    2 publications · 23 citations

    2

    h-index

  4. Wellcome Open Research

    2 publications · 74 citations

    2

    h-index

  5. Journal of Statistical Software

    JSS · 2 publications · 53 citations

    2

    h-index

1–5