Truncated Data Analysis

Truncated Data Analysis is a statistical methodology within nonparametric survival analysis that specifically addresses data where observation is conditioned on the occurrence of events within a certain time window, thereby excluding subjects whose event times fall outside the observable range, distinguishing it from censoring by involving a sampling mechanism that omits entire observations rather than partial information.

310

Publications

31.1K

Citations

543

Authors

330

Institutions

Publications per year

2017–2026

46

Authors

543

  1. PS
    Pao‐Sheng Shen

    Tunghai University, Taiwan

    15 publications · 335 citations

    13

    h-index

  2. JD
    Jacobo de Uña‐Álvarez

    Universidade de Vigo, Spain

    8 publications · 243 citations

    8

    h-index

  3. AC
    Arthur Cohen

    University of Georgia, United States

    7 publications · 701 citations

    7

    h-index

  4. MW
    Mei‐Cheng Wang

    Johns Hopkins University, United States

    7 publications · 589 citations

    7

    h-index

  5. RA
    Rebecca A. Betensky

    Harvard University, United States

    6 publications · 196 citations

    6

    h-index

1–5 of 543

Venues

  1. Journal of the American Statistical Association

    36 publications · 3.4K citations

    24

    h-index

  2. Biometrics

    18 publications · 1.2K citations

    16

    h-index

  3. Technometrics

    18 publications · 11.1K citations

    15

    h-index

  4. Computational Statistics & Data Analysis

    CSDA · 11 publications · 277 citations

    10

    h-index

  5. Biometrika

    10 publications · 774 citations

    10

    h-index

1–5