Bootstrap Variance Component Inference

Bootstrap Variance Component Inference is a statistical methodology that uses resampling techniques to estimate the variability of variance components in hierarchical or mixed-effects models by repeatedly sampling from the observed data to approximate the sampling distribution of the component estimates.

6

Publications

253

Citations

10

Authors

12

Institutions

Publications per year

2017–2026

0

Authors

10

  1. GC
    Gregory Campbell

    National Institutes of Health, United States

    1 publications · 126 citations

    1

    h-index

  2. BT
    Bruce Thompson

    Massachusetts General Hospital, United States

    1 publications · 76 citations

    1

    h-index

  3. OP
    Odile Pons

    Institut National de la Recherche Agronomique, Morocco

    1 publications · 14 citations

    1

    h-index

  4. SV
    Sergey V. Beiden

    Center for Devices and Radiological Health, United States

    1 publications · 126 citations

    1

    h-index

  5. RF
    Robert F. Wagner

    Center for Devices and Radiological Health, United States

    1 publications · 126 citations

    1

    h-index

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Venues

  1. 1

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  2. Academic Radiology

    1 publications · 126 citations

    1

    h-index

  3. Educational and Psychological Measurement

    1 publications · 15 citations

    1

    h-index

  4. Heredity

    1 publications · 14 citations

    1

    h-index

  5. Economics Letters

    1 publications · 12 citations

    1

    h-index

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