Missing Data Impact Assessment

Missing Data Impact Assessment is a methodological procedure within sample size planning that evaluates the extent to which missing data may compromise statistical power, bias estimates, and overall validity of study conclusions.

30

Publications

864

Citations

105

Authors

65

Institutions

Publications per year

2017–2026

9

Authors

105

  1. CB
    Charles B. Hall

    Albert Einstein College of Medicine, United States

    1 publications · 14 citations

    1

    h-index

  2. AA
    Ahmed Al‐Emran

    University of Calgary, Canada

    1 publications · 60 citations

    1

    h-index

  3. RP
    Ronny Pipes

    The University of Texas Southwestern Medical Center, United States

    1 publications · 16 citations

    1

    h-index

  4. MK
    Mimi Kim

    Albert Einstein College of Medicine, United States

    1 publications · 14 citations

    1

    h-index

  5. MC
    Matthew C. Holtman

    National Board of Medical Examiners, United States

    1 publications · 17 citations

    1

    h-index

1–5 of 105

Venues

  1. Psychological Methods

    1 publications · 41 citations

    1

    h-index

  2. American Economic Review

    1 publications · 51 citations

    1

    h-index

  3. Journal of Biopharmaceutical Statistics

    JBS · 1 publications · 104 citations

    1

    h-index

  4. 1

    h-index

  5. Policy Sciences

    1 publications · 16 citations

    1

    h-index

1–5