Null Effect Detection

Null Effect Detection is a type of metric selection method that specifically identifies the absence of a measurable effect or difference in empirical data, thereby distinguishing itself from other metric selection approaches by its focus on validating non-significance or invariance within experimental or observational outcomes.

55

Publications

3.3K

Citations

143

Authors

95

Institutions

Publications per year

2017–2026

16

Authors

143

  1. RW
    Robert W. Fairlie

    University of California, Santa Cruz, United States

    3 publications · 189 citations

    3

    h-index

  2. CM
    Constantin Mang

    Ifo Institute for Economic Research, Germany

    3 publications · 250 citations

    3

    h-index

  3. OF
    Oliver Falck

    Ifo Institute for Economic Research, Germany

    2 publications · 207 citations

    2

    h-index

  4. TG
    T. G. Barnes

    University of Kentucky, United States

    2 publications · 255 citations

    2

    h-index

  5. WG
    W. Gieren

    University of Concepción, Chile

    2 publications · 255 citations

    2

    h-index

1–5 of 143

Venues

  1. SSRN Electronic Journal

    Repository · 4 publications · 163 citations

    4

    h-index

  2. PLoS ONE

    2 publications · 128 citations

    2

    h-index

  3. Astronomy and Astrophysics

    2 publications · 266 citations

    2

    h-index

  4. Journal of Applied Psychology

    2 publications · 90 citations

    2

    h-index

  5. Applied Cognitive Psychology

    ACP · 1 publications · 10 citations

    1

    h-index

1–5