Left-truncated Data Analysis

Left-Truncated Data Analysis is a statistical methodology within survival analysis that specifically addresses data in which observations are only included if they exceed a certain threshold time, thereby accounting for the bias introduced by the absence of records before the truncation point.

98

Publications

5.2K

Citations

385

Authors

158

Institutions

Publications per year

2017–2026

34

Authors

385

  1. PS
    Pao‐Sheng Shen

    Tunghai University, Taiwan

    7 publications · 95 citations

    7

    h-index

  2. MW
    Mei‐Cheng Wang

    Johns Hopkins University, United States

    5 publications · 415 citations

    5

    h-index

  3. JQ
    Jing Qian

    University of Massachusetts Amherst, United States

    3 publications · 44 citations

    3

    h-index

  4. RA
    Rebecca A. Betensky

    Harvard University, United States

    3 publications · 44 citations

    3

    h-index

  5. ÁM
    Álvaro Muñoz

    Johns Hopkins University, United States

    2 publications · 225 citations

    2

    h-index

1–5 of 385

Venues

  1. Biometrics

    9 publications · 294 citations

    9

    h-index

  2. Biometrika

    6 publications · 630 citations

    6

    h-index

  3. Statistics & Probability Letters

    5 publications · 76 citations

    5

    h-index

  4. Statistics in Medicine

    5 publications · 121 citations

    5

    h-index

  5. Computational Statistics & Data Analysis

    CSDA · 4 publications · 77 citations

    4

    h-index

1–5