Methods for testing statistical differences between groups in medical research: statistical standard and guideline of Life Cycle Committee

In medical research, when independent variables are categorical (i.e., dividing groups), statistical analysis is often required. This situation mostly occurs on randomized controlled trials and observational studies that have multiple patient groups. Also, when analyzing continuous independent variables in a single patient group, breakpoints can be set to categorize them into several groups. To test statistical differences between groups, a proper statistical method should be selected, mainly based on the type of dependent variable (i.e., result) and context. The most commonly used tests include t-test, analysis of variance (ANOVA), non-parametric tests, chi-square, and post-hoc analyses. In this article, the author explains statistical methods and which methods should be selected. Through this paper, researchers will be able to understand statistical methods and receive help when choosing and performing statistical analysis. The article can also be used as a reference when researchers justify their statistical approaches when publishing research results.