Interval-censored Data Simulation

Interval-Censored Data Simulation is a computational methodology in survival analysis that generates synthetic datasets where event times are only known to lie within specific time intervals, thereby enabling the evaluation and validation of statistical models under interval censoring conditions.

95

Publications

4.4K

Citations

203

Authors

135

Institutions

Publications per year

2017–2026

15

Authors

203

  1. JS
    Jianguo Sun

    University of Missouri, United States

    10 publications · 344 citations

    10

    h-index

  2. WP
    Wei Pan

    University of Minnesota, United States

    5 publications · 254 citations

    5

    h-index

  3. DM
    Dianne M. Finkelstein

    Massachusetts General Hospital, United States

    4 publications · 175 citations

    4

    h-index

  4. JW
    John Williamson

    Centers for Disease Control and Prevention, United States

    3 publications · 103 citations

    3

    h-index

  5. RA
    Rebecca A. Betensky

    Harvard University, United States

    3 publications · 98 citations

    3

    h-index

1–5 of 203

Venues

  1. Statistics in Medicine

    19 publications · 787 citations

    17

    h-index

  2. Biometrics

    7 publications · 276 citations

    7

    h-index

  3. Journal of Statistical Computation and Simulation

    JSCS · 6 publications · 217 citations

    6

    h-index

  4. Journal of Computational and Graphical Statistics

    JCGS · 5 publications · 229 citations

    5

    h-index

  5. Biometrical Journal

    3 publications · 92 citations

    3

    h-index

1–5