The importance of statistical power and sample size estimation in biostatistics cannot be underestimated. Having the optimal sample size of a study is critical in fulfilling the objectives of biostatistics research. Often calculating the sample size is a challenging task due to the difficulties of determining the appropriate number of units that should be incorporated in a study. Statistical power and sample size calculations facilitate the creation of optimal sample size in biostatistics resulting in the generation of relevant results.
Statistical power has significant influence over the calculation of a sample size. According to Hazra, and Gogtay (2016), statistical power refers to the possibility of obtaining statistically significant results in a study; and avoiding the occurrence of Type I and Type II errors that are commonly reported in biostatistics research. Type 1 error is also known as a false positive; it occurs when a study finds that there are differences between two groups leading to the rejection of the null hypothesis. On the other hand, Type II error is a false negative that occurs when research finding shows the existence of significant differences between populations, while in reality they are non-existent (Columb, & Atkinson, 2015). A high statistical power leads to the selection of a larger sample, while low statistical power leads to the creation of a smaller sample size of a study.
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Statistical power is sued differently in qualitative and quantitative studies. For example, statistical power is used in quantitative clinical studies to determine the number of patients and medical personnel that should be included in the research. For qualitative studies like assessing the effectiveness of intervention toolkits, the statistical power is essential in determining the number of interviews or questionnaires that should be used to gather the relevant information. Therefore, it is vital to use the correct statistical power to design an appropriate sample size.
References
Columb, M. O., & Atkinson, M. S. (2015). Statistical analysis: sample size and power estimations. Bja Education , 16 (5), 159-161.
Hazra, A., & Gogtay, N. (2016). Biostatistics series module 5: Determining sample size. Indian journal of dermatology , 61 (5), 496.
