Focus on Data: Statistical Design of Experiments and Sample Size Selection Using Power Analysis
Focus on Data: Statistical Design of Experiments and Sample Size Selection Using Power Analysis
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DOI：
10.1167/iovs.61.8.11
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发表时间：
2020-07-01
影响因子：
4.4
通讯作者：
Kardon, Randy H.
中科院分区：
文献类型：
--
作者：
Ledolter, Johannes;Kardon, Randy H.
目的.为视觉科学家提供关于如何优化设计实验以及如何选择适当样本量的信息，这通常被称为功效分析。提供了统计学指南，概述了实验设计的良好原则，包括重复，随机化，受试者的区组或分组，多因素设计和序贯实验方法。此外，功率分析的原则，计算所需的样本量概述了不同的实验设计和例子，计算功率和影响它的因素。显示了功效、样本量和标准化效应量之间的相互作用。还提供了以下结果：样本量随功效而增加，样本量随可检测差异的降低而增加，样本量与方差成比例增加，双侧检验（不优先考虑平均值是否增加或减少）需要比单侧检验更大的样本量。这篇评论概述了良好的实验设计的原则和方法的功率分析的典型样本量的计算，视觉科学家在设计实验时遇到的正常和非高斯样本分布。
PURPOSE. To provide information to visual scientists on how to optimally design experiments and how to select an appropriate sample size, which is often referred to as a power analysis.METHODS. Statistical guidelines are provided outlining good principles of experimental design, including replication, randomization, blocking or grouping of subjects, multifactorial design, and sequential approach to experimentation. In addition, principles of power analysis for calculating required sample size are outlined for different experimental designs and examples are given for calculating power and factors influencing it.RESULTS. The interaction between power, sample size and standardized effect size are shown. The following results are also provided: sample size increases with power, sample size increases with decreasing detectable difference, sample size increases proportionally to the variance, and two-sided tests, without preference as to whether the mean increases or decreases, require a larger sample size than one-sided tests.CONCLUSIONS. This review outlines principles for good experimental design and methods for power analysis for typical sample size calculations that visual scientists encounter when designing experiments of normal and non-Gaussian sample distributions.