Statistical data presentation: a primer for rheumatology researchers.

Area of Science:

• Biostatistics
• Biomedical Data Analysis
• Research Methodology

Background:

• Effective statistical presentation is fundamental for interpreting biomedical data and drawing valid conclusions.
• Understanding data distribution (normal vs. non-normal) and variable types (continuous vs. discrete) dictates appropriate statistical methods.

Purpose of the Study:

• To provide an overview of essential statistical considerations for biomedical data analysis.
• To guide researchers in selecting appropriate statistical techniques for different data types and research questions.

Main Methods:

• Discusses the importance of assessing data normality for parametric versus non-parametric analysis selection.
• Highlights the use of means with standard deviations (SD) for normal distributions and medians for non-normal distributions.
• Explains the roles of standard error, univariable and multivariable analyses (linear/logistic regression), and correlation/concordance statistics.

Main Results:

• Recommends prior sample size calculation to ensure adequate study power.
• Outlines statistical considerations for systematic reviews, including meta-analysis, heterogeneity, and publication bias assessment.
• Emphasizes that statistical errors contribute significantly to research retractions, underscoring the need for rigorous statistical practices.

Conclusions:

• Appropriate statistical analysis is mandatory throughout study planning and data analysis to ensure research integrity.
• Correct application of statistical methods enhances the reliability of findings and reduces the risk of erroneous conclusions and retractions.