Comparing baseline characteristics between groups: an introduction to the CBCgrps package

Area of Science:

• Biostatistics
• Observational Study Design
• Data Mining

Background:

• Comparing baseline characteristics between study groups is standard in observational research.
• Manual table generation is feasible for limited variables but error-prone and time-consuming with large datasets from Electronic Health Records (EHR) and big data mining.
• Automating this process is crucial for efficient and accurate analysis of extensive data.

Discussion:

• The CBCgrps R package automates the creation of baseline characteristic comparison tables.
• It addresses the challenges of manual tabulation with big data, enhancing efficiency and reducing errors.
• The package offers two functions: twogrps() for two-group comparisons and multigrps() for multiple-group comparisons.

Key Insights:

• CBCgrps significantly reduces the time and potential for errors in generating baseline characteristic tables.
• The package facilitates more comprehensive analysis by enabling the exploration of a larger number of variables.
• It supports both two-group and multiple-group comparisons, enhancing analytical flexibility.

Outlook:

• Wider adoption of CBCgrps can improve the reproducibility and efficiency of observational studies.
• Future development could include integration with other statistical software or advanced visualization tools.
• This automation supports researchers in leveraging big data for robust clinical insights.