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摘要翻译：
研究人员经常计算测量量的比率。确定比值的置信限是困难的，适当的方法往往是未知的。描述了适当的方法(Fieller，Taylor，特殊的引导方法）。对Fieller方法给出了简单的几何解释。蒙特卡罗模拟表明，这些方法何时是适当的，最常用的方法（指数法和零方差法）可以导致较大的自由偏离期望的置信度水平。讨论了当我们可以使用标准回归或测量误差模型时，当我们必须求助于异方差数据的特定模型时。最后，重复了一个古老的警告，即如果我们使用比率，我们应该意识到虚假相关性的问题。
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英文标题：
《Ratios: A short guide to confidence limits and proper use》
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作者：
Volker H. Franz
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最新提交年份：
2007
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分类信息：
一级分类：Statistics 统计学
二级分类：Applications 应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
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一级分类：Statistics 统计学
二级分类：Methodology 方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
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英文摘要：
Researchers often calculate ratios of measured quantities. Specifying confidence limits for ratios is difficult and the appropriate methods are often unknown. Appropriate methods are described (Fieller, Taylor, special bootstrap methods). For the Fieller method a simple geometrical interpretation is given. Monte Carlo simulations show when these methods are appropriate and that the most frequently used methods (index method and zero-variance method) can lead to large liberal deviations from the desired confidence level. It is discussed when we can use standard regression or measurement error models and when we have to resort to specific models for heteroscedastic data. Finally, an old warning is repeated that we should be aware of the problems of spurious correlations if we use ratios.
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PDF链接：
https://arxiv.org/pdf/710.2024
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