Kosin Med J.  2025 Mar;40(1):21-30. 10.7180/kmj.24.160.

Common statistical methods used in medical research

• Yang HJ
• Lee HS

• KMID: 2566128
• DOI: http://doi.org/10.7180/kmj.24.160

Abstract

This paper aims to review the statistical methods that are widely used in medical and clinical research. Statistical analysis is crucial for ensuring the reliability of research results; therefore, methods should be carefully tailored to research interests and objectives, depending on the type and characteristics of the data. This paper explains various types of data, discusses how to confirm whether the data satisfy these methods’ specific assumptions, and elucidates the meaning and interpretation of univariable and multivariable analysis. Finally, it presents corresponding examples to help other researchers understand how these methods are applied in real-world studies and select appropriate methods that ensure both research quality and reliability.

Keyword

Categorical data; Continuous data; Multivariable analysis; Univariable analysis

Figure

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  Fig. 1. Visualization of associations between variables. (A) Visualization of the relationship between categorical and continuous variables when using the parametric method: a bar graph with the two groups’ mean and standard deviation values is commonly used to visualize the results of comparing means between groups. Each bar represents the mean of the corresponding group, and the whiskers indicate the standard deviation. (B) Visualization of the relationship between categorical and continuous variables when using the non-parametric method: a box plot with the median (interquartile range) of the two groups is commonly used to visualize the results of comparing means between groups. (C) Visualization of the relationship between continuous and continuous variables: a scatter plot is frequently presented with the results of correlation analysis or univariable linear regression to illustrate the association between two continuous variables. (D) Visualization of the relationship between categorical and categorical variables: a bar graph representing the outcome rates of groups is typically plotted with results from the chi-square test. The proportion of each outcome is shown by each bar.

Reference

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