Measurement Error Decomposition

Measurement Error Decomposition is a methodological framework within facet design and G-study design that partitions total measurement error into distinct variance components attributable to specific facets of measurement, thereby enabling the systematic evaluation of reliability and precision in observational or experimental designs.

53

Publications

2.1K

Citations

205

Authors

108

Institutions

Publications per year

2017–2026

21

Authors

205

  1. WA
    Walter A. Petersen

    Marshall Space Flight Center, United States

    2 publications · 203 citations

    2

    h-index

  2. SL
    Susanna Loeb

    Stanford University, United States

    2 publications · 48 citations

    2

    h-index

  3. WS
    Wei S. Schneider

    University of Iowa, United States

    2 publications · 37 citations

    2

    h-index

  4. PK
    Pierre‐Emmanuel Kirstetter

    NOAA National Severe Storms Laboratory, United States

    2 publications · 147 citations

    2

    h-index

  5. DB
    David B. Wolff

    Goddard Space Flight Center, United States

    2 publications · 88 citations

    2

    h-index

1–5 of 205

Venues

  1. Remote Sensing

    3 publications · 94 citations

    3

    h-index

  2. Journal of Statistical Planning and Inference

    3 publications · 91 citations

    3

    h-index

  3. Geophysical Research Letters

    2 publications · 43 citations

    2

    h-index

  4. Journal of Hydrology

    2 publications · 54 citations

    2

    h-index

  5. SSRN Electronic Journal

    Repository · 2 publications · 40 citations

    2

    h-index

1–5