Process / pipelinestudy-design

Statistička moć i veličina uzorka

Statistička moć je verovatnoća detektovanja istinskog efekta ako on postoji (1 − β). Analiza moći određuje veličinu uzorka potrebnu za detektovanje hipotezirane veličine efekta sa specificiranim stopama greške tipa I (α) i greške tipa II (β). Uvedena od strane Jacoba Cohena (1988), analiza moći je fundamentalna za dizajn istraživanja: studije sa nedovoljnom moći proizvode preuveličane procene veličine efekta i malo je verovatno da će se replicirati. Standardna referentna vrednost je 80% moći (β = 0,20), mada kritične studije mogu zahtevati 90% moći.

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Izvori

  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/sr/research-statistics/statistical-power

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ScholarGateStatistical Power and Sample Size (Statistical Power Analysis and Sample Size Determination for Research Studies). Preuzeto 2026-06-15 sa https://scholargate.app/sr/research-statistics/statistical-power · Skup podataka: https://doi.org/10.5281/zenodo.20539026