Cluster randomized trial (CRT) is one of the most common design for complex intervention. This paper mainly introduced:the definition of CRT, two designs of CRT including the completely randomization and the restricted randomization (such as stratified randomization and matching randomization), and the statistical analysis methods (such as the general statistical analysis and mixed effect model/multi-level model). This paper also introduced how to estimate the sample size of a CRT, how to report a CRT, and how to apply it into a clinical or community study.
This paper mainly introduces the design, advantages, disadvantages and its application of single case of randomized controlled trials (N-of-1 trials), and also introduces the commonly used data analysis methods of N-of-1 trials including nonparametric test and parameter test methods (t-test, paired t-test, analysis of variance), mixed-effects model, and meta-analysis. N-of-1 trials are suitable for individualized treatment, and could be expected to be widely used in the research of modern medicine and traditional Chinese medicine.
Meta-analysis of survival data is becoming more and more popular. The data could be extracted from the original literature, such as hazard ratio (HR) and its 95% confidence interval, the difference of actual frequency and theoretical frequency (O - E) and its standard deviation. The data can be used to calculate the combined HR using Review Manager (RevMan), Stata and R softwares. RevMan software is easy to learn, but there are some limitations. Stata and R software are powerful and flexible, and they are able to draw a variety of graphics, however, they need to be programmed to achieve.
The CONSORT extension for reporting N-of-1 trials (CENT 2015) is designed to guide N-of-1 and series N-of-1 reporting. This study introduced the terminology (period, block or pair, sequence, washout period, and run-in period), the scope, the checklist and the diagram of CENT 2015 and demonstrated the complete guide frame for N-of-1, and thus to provide reference for relevant studies and improve the reporting quality of N-of-1 in China.
The standards for reporting of diagnostic accuracy (STARD) was developed for guiding the reporting of diagnostic accuracy studies. Its newest version was published in 2015. The study mainly introduced the checklist, terminology, and diagram of the STARD 2015. It is hoped that domestic researchers could use the STARD 2015 to guide the implementation and reporting of their diagnostic accuracy studies, so as to improve the reporting quality of diagnostic accuracy studies.