Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls

Key Points

• The central aim is to explore the effective use of multiple imputation to handle missing data in research.
• Review of statistical literature on multiple imputation.
• Analysis of case studies in epidemiological and clinical settings.
• Guidelines for appropriate reporting and application of the method.
• Multiple imputation can improve accuracy in data analysis.
• Proper reporting enhances credibility in research findings.
• Common pitfalls include incorrect assumptions about missing data.