Interval-censored Data Analysis

Interval-Censored Data Analysis is a statistical methodology within nonparametric survival analysis that specifically addresses the estimation of time-to-event distributions when the exact event times are not observed but are known to lie within certain intervals.

584

Publications

27K

Citations

1.2K

Authors

606

Institutions

Publications per year

2017–2026

105

Authors

1.2K

  1. JS
    Jianguo Sun

    University of Missouri, United States

    45 publications · 1.4K citations

    21

    h-index

  2. DM
    Dianne M. Finkelstein

    Massachusetts General Hospital, United States

    11 publications · 1.4K citations

    11

    h-index

  3. RJ
    Richard J. Cook

    University of Waterloo, Canada

    10 publications · 243 citations

    10

    h-index

  4. LW
    Lianming Wang

    University of South Carolina, United States

    10 publications · 413 citations

    10

    h-index

  5. RA
    Rebecca A. Betensky

    Harvard University, United States

    10 publications · 511 citations

    10

    h-index

1–5 of 1.2K

Venues

  1. Biometrics

    67 publications · 4.5K citations

    38

    h-index

  2. Statistics in Medicine

    68 publications · 2.6K citations

    30

    h-index

  3. Journal of the American Statistical Association

    24 publications · 1.5K citations

    20

    h-index

  4. Computational Statistics & Data Analysis

    CSDA · 29 publications · 846 citations

    18

    h-index

  5. Biometrika

    20 publications · 1.4K citations

    17

    h-index

1–5