Sürücü B, Koç E
Department of Statistics, Middle East Technical University, Ankara, Turkey.
Clin Exp Dermatol. 2008 May;33(3):239-42. doi: 10.1111/j.1365-2230.2007.02629.x. Epub 2007 Dec 18.
Assuming a statistical distribution is one of the key points before conducting a statistical analysis. Goodness-of-fit tests are used to assess the validity of an assumed statistical distribution. In dermatological research, the goodness-of-fit tests used are less powerful.
We recommend the use of some specific goodness-of-fit tests for various distributions. A graphical technique called quantile-quantile plotting is introduced as an additional tool to assess the validity of an assumed distribution. We show why one should be careful in selecting a goodness-of-fit method by giving some relevant examples.
Goodness-of-fit tests for testing normal and non-normal distributions are introduced. Quantile-quantile plots were constructed, and we conducted a simulation study for testing normality.
We found that the Shapiro-Wilk statistic is the most powerful test overall to test for normal distribution. Quantile-quantile plotting is a very effective graphical technique to identify a distribution for a dataset.
The use of the Shapiro-Wilk test and quantile-quantile plotting is recommended for testing normality.
在进行统计分析之前，假设一种统计分布是关键要点之一。拟合优度检验用于评估假设的统计分布的有效性。在皮肤病学研究中，所使用的拟合优度检验效力较低。
我们推荐针对各种分布使用一些特定的拟合优度检验。引入一种名为分位数 - 分位数绘图的图形技术作为评估假设分布有效性的额外工具。我们通过给出一些相关示例来说明为何在选择拟合优度方法时应谨慎。
介绍了用于检验正态和非正态分布的拟合优度检验。构建了分位数 - 分位数图，并进行了用于检验正态性的模拟研究。
我们发现，总体而言，夏皮罗 - 威尔克统计量是检验正态分布最有效的检验方法。分位数 - 分位数绘图是识别数据集分布的一种非常有效的图形技术。
建议使用夏皮罗 - 威尔克检验和分位数 - 分位数绘图来检验正态性。
