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Power Analysis, Sample Size, and Assessment of Statistical Assumptions-Improving the Evidential Value of Lighting Research

机译：功效分析，样本量和统计假设评估-改善照明研究的证据价值

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摘要

The reporting of accurate and appropriate conclusions is an essential aspect of scientific research, and failure in this endeavor can threaten the progress of cumulative knowledge. This is highlighted by the current reproducibility crisis, and this crisis disproportionately affects fields that use behavioral research methods, as in much lighting research. A sample of general and topic-specific lighting research papers was reviewed for information about sample sizes and statistical reporting. This highlighted that lighting research is generally underpowered and, given median sample sizes, is unlikely to be able to reveal small effects. Lighting research most commonly uses parametric statistical tests, but assessment of test assumptions is rarely carried out. This risks the inappropriate use of statistical tests, potentially leading to type I and type II errors. Lighting research papers also rarely report measures of effect size, and this can hamper cumulative science and power analyses required to determine appropriate sample sizes for future research studies. Addressing the issues raised in this article related to sample sizes, statistical test assumptions, and reporting of effect sizes can improve the evidential value of lighting research.
机译：报告正确和适当的结论是科学研究的重要方面，而这项工作的失败会威胁到累积知识的发展。当前的可再现性危机突显了这一点，与许多照明研究一样，该危机对使用行为研究方法的领域造成了不成比例的影响。审查了常规和特定主题照明研究论文的样本，以获取有关样本量和统计报告的信息。这突出表明，照明研究通常动力不足，并且鉴于样本量的中值，不太可能显示出较小的影响。照明研究最常使用参数统计测试，但是很少对测试假设进行评估。这冒着不适当使用统计测试的风险，有可能导致I型和II型错误。照明研究论文也很少报告效应量的度量，这会妨碍为确定未来研究的合适样本量而进行的累积科学和功效分析。解决本文中提出的与样本大小，统计测试假设和效果大小报告有关的问题，可以提高照明研究的证据价值。

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