Process / pipelinestudy-design
统计功效与样本量
统计功效是指当真实效应存在时，检测到该效应的概率（1 − β）。功效分析用于确定在指定的I类错误（α）和II类错误（β）率下，检测假设效应量所需的样本量。由 Jacob Cohen (1988) 提出的功效分析是研究设计的基石：功效不足的研究会产生夸大的效应量估计值，并且不太可能复制。标准基准是80%的功效（β = 0.20），尽管关键性研究可能需要90%的功效。
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来源
- Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Lawrence Erlbaum Associates. ISBN: 0-8058-0283-5
- 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 ↗
- 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 ↗
如何引用本页
ScholarGate. (2026, June 3). Statistical Power Analysis and Sample Size Determination for Research Studies. ScholarGate. https://scholargate.app/zh/research-statistics/statistical-power
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