Confidence Interval Methodology

Confidence Interval Methodology is a statistical inference framework belonging to the class of estimation techniques, distinguished by its specification of a range of values derived from sample data that, under repeated sampling, is expected to contain the true population parameter with a defined probability.

840

Publications

80.8K

Citations

1.3K

Authors

661

Institutions

Publications per year

2017–2026

74

Authors

1.3K

  1. DG
    Douglas G. Bonett

    Iowa State University, United States

    11 publications · 1.9K citations

    11

    h-index

  2. RK
    Richard K. Burdick

    Arizona State University, United States

    9 publications · 376 citations

    9

    h-index

  3. GZ
    Guangyong Zou

    Western University, Canada

    7 publications · 1.1K citations

    7

    h-index

  4. AJ
    Anthony J. Hayter

    Georgia Institute of Technology, United States

    7 publications · 134 citations

    7

    h-index

  5. PK
    Paul Kabaila

    La Trobe University, Australia

    6 publications · 120 citations

    6

    h-index

1–5 of 1.3K

Venues

  1. Journal of the American Statistical Association

    66 publications · 13.1K citations

    33

    h-index

  2. Statistics in Medicine

    45 publications · 10.8K citations

    28

    h-index

  3. Biometrics

    31 publications · 3.1K citations

    26

    h-index

  4. The American Statistician

    28 publications · 1.1K citations

    18

    h-index

  5. Biometrika

    22 publications · 6.4K citations

    17

    h-index

1–5