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Sample size: how many patients are necessary?

P M Fayers, D Machin

British Journal of Cancer

|July 1, 1995

Summary

This summary is machine-generated.

This study reviews the critical need for adequate sample size calculations in research, particularly for survival studies and prognostic factor analysis. Ensuring sufficient sample sizes prevents misleading results and strengthens scientific validity.

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Area of Science:

Biostatistics
Clinical Trials Methodology
Epidemiology

Background:

The necessity of robust sample size calculations in research is underscored, addressing common arguments against underpowered studies.
Existing challenges in accurately estimating sample sizes are explored, with a specific focus on survival analysis.

Discussion:

The principles discussed for sample size estimation in survival studies are broadly applicable across various research designs.
Prognostic factor analysis is highlighted as an area frequently plagued by inadequate study sizes, leading to unreliable findings.

Key Insights:

Underpowered studies, particularly those with small sample sizes, often yield misleading results and lack statistical power.
Accurate sample size determination is crucial for the validity and interpretability of research outcomes.

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The challenges in sample size estimation necessitate careful consideration in study design.

Outlook:

Future research should emphasize rigorous sample size planning to enhance the reliability of scientific evidence.
Promoting best practices in sample size calculation can mitigate the risk of underpowered studies across disciplines.
Further investigation into advanced sample size methodologies may address complex study designs more effectively.