Missing Data Diagnostics

Missing Data Diagnostics is a systematic methodological framework used to assess the patterns, mechanisms, and implications of missing data within a dataset, distinguishing itself by providing formal criteria and analytical tools to determine the nature and extent of missingness in order to guide appropriate handling strategies.

53

Publications

4.7K

Citations

151

Authors

92

Institutions

Publications per year

2017–2026

9

Authors

151

  1. RR
    Roozbeh Razavi‐Far

    University of Windsor, Canada

    2 publications · 76 citations

    2

    h-index

  2. HZ
    Hongtu Zhu

    University of North Carolina at Chapel Hill, United States

    2 publications · 27 citations

    2

    h-index

  3. JS
    Jeffrey S. Simonoff

    New York University, United States

    2 publications · 42 citations

    2

    h-index

  4. TE
    Trivellore E. Raghunathan

    University of Michigan, United States

    2 publications · 76 citations

    2

    h-index

  5. MS
    Mehrdad Saif

    University of Windsor, Canada

    2 publications · 76 citations

    2

    h-index

1–5 of 151

Venues

  1. Biometrics

    4 publications · 218 citations

    4

    h-index

  2. Educational and Psychological Measurement

    2 publications · 134 citations

    2

    h-index

  3. Journal of Clinical Epidemiology

    2 publications · 94 citations

    2

    h-index

  4. Journal of Management

    JOM · 2 publications · 57 citations

    2

    h-index

  5. Biometrika

    2 publications · 22 citations

    2

    h-index

1–5