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Process / pipelinestudy-design

Statistisk styrke og stikprøvestørrelse

Statistisk styrke er sandsynligheden for at detektere en sand effekt, hvis den eksisterer (1 − β). Styrkeanalyse bestemmer den stikprøvestørrelse, der kræves for at detektere en hypotetisk effektstørrelse med specificerede Type I-fejl (α) og Type II-fejl (β) rater. Introduceret af Jacob Cohen (1988) er styrkeanalyse fundamental for forskningsdesign: underpowered studier producerer oppustede estimater af effektstørrelse og er usandsynlige at kunne replikeres. Standardbenchmark er 80% styrke (β = 0.20), selvom kritiske studier kan kræve 90% styrke.

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Kilder

  1. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 0-8058-0283-5
  2. Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A Flexible Statistical Power Analysis Program for the Social, Behavioral, and Biomedical Sciences. Behavior Research Methods, 39(2), 175–191. DOI: 10.3758/BF03193146
  3. Button, K. S., Ioannidis, J. P. A., Mokrysz, C., Nosek, B. A., Flint, J., Robinson, E. S. J., & Munafò, M. R. (2013). Power failure: why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience, 14(5), 365–376. DOI: 10.1038/nrn3475

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ScholarGate. (2026, June 3). Statistical Power Analysis and Sample Size Determination for Research Studies. ScholarGate. https://scholargate.app/da/research-statistics/statistical-power

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ScholarGateStatistical Power and Sample Size (Statistical Power Analysis and Sample Size Determination for Research Studies). Hentet 2026-06-15 fra https://scholargate.app/da/research-statistics/statistical-power · Datasæt: https://doi.org/10.5281/zenodo.20539026