Two-factor designs are very 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 experimental data under a certain condition (usually one of the experimental conditions that are formed by the complete combination of the levels of the two factors) is allowed in specialty, researchers can use random block design without repeated experiments, balanced incomplete 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 introduces the last two design types by examples.

Key words: statistics, medical, research design, factor analysis, statistical