Ottenbacher K J
University of Texas Medical Branch at Galveston, 77755-1028, USA.
Am J Epidemiol. 1998 Apr 1;147(7):615-9. doi: 10.1093/oxfordjournals.aje.a009501.
Epidemiologic and public health researchers frequently include several dependent variables, repeated assessments, or subgroup analyses in their investigations. These factors result in multiple tests of statistical significance and may produce type 1 experimental errors. This study examined the type 1 error rate in a sample of public health and epidemiologic research. A total of 173 articles chosen at random from 1996 issues of the American Journal of Public Health and the American Journal of Epidemiology were examined to determine the incidence of type 1 errors. Three different methods of computing type 1 error rates were used: experiment-wise error rate, error rate per experiment, and percent error rate. The results indicate a type 1 error rate substantially higher than the traditionally assumed level of 5% (p < 0.05). No practical or statistically significant difference was found between type 1 error rates across the two journals. Methods to determine and correct type 1 errors should be reported in epidemiologic and public health research investigations that include multiple statistical tests.
流行病学和公共卫生研究人员在其调查中经常纳入多个因变量、重复评估或亚组分析。这些因素导致了多次统计显著性检验，并可能产生I类实验误差。本研究考察了公共卫生和流行病学研究样本中的I类错误率。从1996年的《美国公共卫生杂志》和《美国流行病学杂志》中随机选取了173篇文章，以确定I类错误的发生率。使用了三种不同的计算I类错误率的方法：实验性错误率、每次实验的错误率和错误率百分比。结果表明，I类错误率大大高于传统假设的5%水平（p < 0.05）。在这两本杂志的I类错误率之间未发现实际的或统计学上的显著差异。在包括多次统计检验的流行病学和公共卫生研究调查中，应报告确定和纠正I类错误的方法。
