Multiple Imputation

Multiple Imputation is a statistical technique for handling missing data that belongs to the class of imputation methods, distinguished by generating multiple plausible values for each missing entry to reflect uncertainty, thereby producing several complete datasets that are analyzed separately and combined to yield valid inferences.

2.9K

Publications

313.8K

Citations

11.4K

Authors

3.3K

Institutions

Publications per year

2017–2026

1.2K

Authors

11.4K

  1. IR
    Ian R. White

    MRC Biostatistics Unit, United Kingdom

    41 publications · 25.5K citations

    35

    h-index

  2. DB
    Donald B. Rubin

    Harvard University, United States

    40 publications · 18.4K citations

    34

    h-index

  3. JR
    James R. Carpenter

    London School of Hygiene & Tropical Medicine, United Kingdom

    44 publications · 12.7K citations

    32

    h-index

  4. PR
    Patrick Royston

    MRC Clinical Trials Unit at UCL, United Kingdom

    26 publications · 27.6K citations

    24

    h-index

  5. JP
    Jerome P. Reiter

    Duke University, United States

    35 publications · 2.6K citations

    23

    h-index

1–5 of 11.4K

Venues

  1. Statistics in Medicine

    158 publications · 23.2K citations

    56

    h-index

  2. BMC Medical Research Methodology

    62 publications · 8.9K citations

    39

    h-index

  3. Journal of the American Statistical Association

    58 publications · 12.9K citations

    37

    h-index

  4. PLoS ONE

    76 publications · 4K citations

    31

    h-index

  5. Statistical Methods in Medical Research

    52 publications · 8.2K citations

    27

    h-index

1–5