How to choose an appropriate experimental design type to arrange research factors and their levels is an important issue in experimental research. Choosing an appropriate design type is directly related to the accuracy and reliability of the research result. When confronting a practical issue, how can researchers choose the most appropriate design type to arrange the experiment based on research objective and specified situation? This article mainly introduces the related contents of the single-group design and the paired design through practical examples.

The general problems existing in the clinical trials of investigational new drugs involve some key aspects such as the guiding principles, research designs, quality controls and statistical analyses. This paper explores the eight general issues in the clinical trials of investigational new drugs and presents precautionary measures with high operability. Research on the clinical trials of investigational new drugs is a complex project, which should be carried out strictly according to the policies, laws, criteria and operating rules set by related agencies. The neglect of research designs and data analyses will lead clinical trials to failure.

Three-factor designs that are unable to examine the interactions include crossover design and Latin square design, which can examine three factors, namely, an experimental factor and two block factors. Although the two design types are not quite frequently used in practical research, an unexpected research effect will be achieved if they are correctly adopted on appropriate occasions. Due to the limit of space, this article introduces two forms of crossover design.

Three-factor designs that are unable to examine the interactions include crossover design and Latin square design, which can examine three factors: an experimental factor and two block factors. Although the two design types are not quite frequently used in practical research, an unexpected research effect will be achieved if they are correctly adopted on appropriate occasions. This article introduced the 3×3 crossover design and the Latin square design by examples.

Multifactor designs that are able to examine the interactions include factorial design, factorial design with a block factor, repeated measurement design; orthogonal design, split-block design, etc. Among all the above design types that are able to examine the interactions, the factorial design is the most commonly used. It is also called the full-factor experimental design, which means that the levels of all the experimental factors involved in the research are completely combined, and k independent repeated experiments are conducted under each experimental condition. The factorial design with a block factor can also examine the influence of a block factor formed by one or more important non experimental factors based on the factorial design. This article introduces the factorial design and the factorial design with a block factor by examples.

Objective To analyze the demographic characteristics,composition characteristics as well as influencing factors of the cost of hospitalization of patients with lung cancer in Gansu Province in order to help reduce their expenses. Methods The basics,healthcare records and expenses of patients diagnosed with lung cancer in a third-level grade-A hospital in Lanzhou were extracted between 2010 and 2014 through the hospital information system(HIS)database.The Wilcoxon rank-sum test was used to analyze the difference of expense composition over the past five years and the difference between subgroups.The forward,backward and stepwise selection method was used to select variables and the multi-linear regression analysis was adopted to explore the influencing factors of the cost of hospitalization.Results A total of 2778 eligible lung cancer patients were collected.The statistical analysis showed that western medicine cost (36.39%)and treatment cost (22.46%)accounted for the most of the total expense.The length of hospital stay was the No.1 influencing factor of the cost of hospitalization,followed by the acceptance of surgery,the year of admission and charge type. Conclusion Regulating drug use,enhancing treatment regimens,giving psychological guidance,strengthening hospital management and improving medical resources allocation may be effective measures to reduce the cost of hospitalization and lighten the economic burden for lung cancer patients in Gansu Province.

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.