Imputation Uncertainty Quantification

Imputation Uncertainty Quantification is a methodological framework within missing data imputation that characterizes the reliability of imputed values by modeling the variability and confidence associated with the imputation process.

78

Publications

7.5K

Citations

279

Authors

132

Institutions

Publications per year

2017–2026

27

Authors

279

  1. BN
    Bin Nan

    University of Michigan, United States

    2 publications · 36 citations

    2

    h-index

  2. ZL
    Zhaobin Liu

    Dalian Maritime University, China

    2 publications · 42 citations

    2

    h-index

  3. SV
    Stef van Buuren

    Netherlands Organisation for Applied Scientific Research, Netherlands

    2 publications · 146 citations

    2

    h-index

  4. SS
    Satish Sharma

    University of Regina, Canada

    2 publications · 42 citations

    2

    h-index

  5. RJ
    Roderick J. A. Little

    University of Michigan, United States

    2 publications · 36 citations

    2

    h-index

1–5 of 279

Venues

  1. Statistics in Medicine

    5 publications · 302 citations

    5

    h-index

  2. BMC Bioinformatics

    2 publications · 430 citations

    2

    h-index

  3. Journal of Clinical Epidemiology

    2 publications · 2.9K citations

    2

    h-index

  4. 2

    h-index

  5. Journal of Hydrology

    2 publications · 40 citations

    2

    h-index

1–5