Imputation Uncertainty

Imputation Uncertainty is the quantification of uncertainty arising from the estimation or substitution of missing data values in scientific datasets, distinguishing it from other forms of uncertainty by specifically characterizing the reliability of imputed values in the context of downstream visualization and analysis.

134

Publications

8K

Citations

521

Authors

278

Institutions

Publications per year

2017–2026

64

Authors

521

  1. SL
    Saskia le Cessie

    Leiden University Medical Center, Netherlands

    2 publications · 180 citations

    2

    h-index

  2. SZ
    Shihua Zhang

    Academy of Mathematics and Systems Science, China

    2 publications · 167 citations

    2

    h-index

  3. RJ
    Roderick J. A. Little

    University of Michigan, United States

    2 publications · 36 citations

    2

    h-index

  4. IR
    Ingo Ruczinski

    Johns Hopkins University, United States

    2 publications · 65 citations

    2

    h-index

  5. HT
    Herbert Thijs

    Hasselt University, Belgium

    2 publications · 64 citations

    2

    h-index

1–5 of 521

Venues

  1. BMC Bioinformatics

    4 publications · 527 citations

    4

    h-index

  2. Statistics in Medicine

    4 publications · 227 citations

    4

    h-index

  3. PLoS ONE

    3 publications · 138 citations

    3

    h-index

  4. Genetic Epidemiology

    3 publications · 75 citations

    3

    h-index

  5. G3 Genes Genomes Genetics

    2 publications · 61 citations

    2

    h-index

1–5