Censored Data Analysis

Censored Data Analysis is a statistical methodology that distinguishes itself by enabling inference on datasets where the observation of the variable of interest is partial or incomplete due to predefined censoring mechanisms, such as time truncation or detection limits, within reliability validation studies.

1.9K

Publications

135.4K

Citations

3.4K

Authors

1.4K

Institutions

Publications per year

2017–2026

298

Authors

3.4K

  1. NB
    N. Balakrishnan

    McMaster University, Canada

    39 publications · 2.5K citations

    25

    h-index

  2. WN
    Wayne Nelson

    General Electric (United States), United States

    15 publications · 1.7K citations

    15

    h-index

  3. JS
    Jianguo Sun

    University of Missouri, United States

    17 publications · 588 citations

    13

    h-index

  4. EC
    Erhard Cramer

    RWTH Aachen University, Germany

    15 publications · 626 citations

    12

    h-index

  5. WQ
    William Q. Meeker

    Iowa State University, United States

    12 publications · 454 citations

    12

    h-index

1–5 of 3.4K

Venues

  1. Journal of the American Statistical Association

    118 publications · 10.6K citations

    51

    h-index

  2. Biometrics

    102 publications · 11.5K citations

    44

    h-index

  3. Biometrika

    97 publications · 11.8K citations

    41

    h-index

  4. Technometrics

    69 publications · 9.6K citations

    37

    h-index

  5. Statistics in Medicine

    91 publications · 8.5K citations

    37

    h-index

1–5