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Practical considerations and methods for determining sample size to estimate a population mean: a narrative review
1Clinical Research Centre, National Institutes of Health, Sarawak General Hospital, Ministry of Health Malaysia, Kuching, Malaysia. mohamadadambujang1980@gmail.com.
Accurate sample size determination is vital for research validity. This paper explains the essential, yet often overlooked, sample size formula for population mean estimation, guiding researchers to enhance study precision and credibility.
Area of Science:
- Biostatistics
- Research Methodology
Background:
- Sample size determination is critical for research validity and precision.
- Many researchers overlook estimation-based sample size formulas, focusing instead on hypothesis testing.
- The classical sample size formula for population mean estimation is essential but often neglected.
Purpose of the Study:
- To review the concept, rationale, and application of the sample size formula for population mean estimation.
- To provide guidance on the theoretical foundation, calculation steps, and appropriate use of this formula.
- To emphasize the importance of this formula in contemporary research for improving study design and credibility.
Main Methods:
- Review of the classical sample size formula for estimating a population mean.
- Explanation of theoretical underpinnings and practical calculation steps.
- Discussion of appropriate contexts for its application in descriptive and estimation studies.
Main Results:
- The paper clarifies the concept and rationale behind the sample size formula for mean estimation.
- It details the practical steps for calculating the required sample size.
- It underscores the formula's relevance across diverse research settings.
Conclusions:
- Proper sample size planning using this formula enhances research design validity.
- Accurate sample size calculation is crucial for improving the quality and credibility of scientific investigations.
- This formula remains a highly relevant and essential tool for researchers focusing on estimation.
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