Hu Liang-ping, Bao Xiao-lei, Guo Chen-yi
Consulting Center of Biomedical Statistics, Academy of Military Medical Sciences, Beijing 100850, China.
Zhong Xi Yi Jie He Xue Bao. 2012 Aug;10(8):853-7. doi: 10.3736/jcim20120804.
Two-factor designs are quite commonly used in scientific research. If the two factors have interactions, research designs like the factorial design and the orthogonal design can be adopted; however, these designs usually require many experiments. If the two factors have no interaction or the interaction is not statistically significant on result in theory and in specialty, and the measuring error of the experimental data under a certain condition (usually it is one of the experimental conditions which is formed by the complete combination of the levels of two factors) is allowed in specialty, researchers can use random block design without repeated experiments, balanced non-complete random block design without repeated experiments, single factor design with a repeatedly measured factor, two-factor design without repeated experiments and two-factor nested design. This article introduced the first three design types with examples.
双因素设计在科学研究中相当常用。如果两个因素存在交互作用,可以采用析因设计和正交设计等研究设计;然而,这些设计通常需要进行大量实验。如果两个因素不存在交互作用,或者在理论和专业上交互作用对结果无统计学意义,并且在专业上允许一定条件下(通常是由两个因素水平的完全组合形成的实验条件之一)实验数据的测量误差,研究人员可以使用无重复实验的随机区组设计、无重复实验的平衡不完全随机区组设计、具有重复测量因素的单因素设计、无重复实验的双因素设计和双因素嵌套设计。本文通过实例介绍了前三种设计类型。