Wang Bokai, Zhou Zhirou, Wang Hongyue, Tu Xin M, Feng Changyong
Departments of Biostatistics and Computational Biology and Anesthesiology, University of Rochester, Rochester, New York, USA.
Family Medicine and Public Health, University of California San Diego, San Diego, California, USA.
Gen Psychiatr. 2019 Jul 9;32(3):e100081. doi: 10.1136/gpsych-2019-100081. eCollection 2019.
The p value has been widely used as a way to summarise the significance in data analysis. However, misuse and misinterpretation of the p value is common in practice. Our result shows that if the model specification is wrong, the distribution of the p value may be inappropriate, which makes the decision based on the p value invalid.
p值已被广泛用作总结数据分析中显著性的一种方式。然而，在实际应用中，p值的误用和错误解读很常见。我们的结果表明，如果模型设定错误，p值的分布可能不合适，这会使基于p值的决策无效。
