Volume 28, Issue 149, July 2024

Optimizing sample size estimation and statistical analysis in health sciences: A comprehensive guide using the S2SAC tool

Mohamad Arif Awang Nawi^♦

Biostatistics Unit, School of Dental Sciences, Health Campus, Universiti Sains Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia

^♦Corresponding Author
Biostatistics Unit, School of Dental Sciences, Health Campus, Universiti Sains Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia

ABSTRACT

Statistical errors in health sciences research can greatly undermine the dependability of study results, negatively impacting clinical decision-making and policy development. This work focuses on the crucial task of minimizing potential statistical errors that arise from inadequate sample size estimation and improper analysis methodologies. The Sample Size & Statistical Analysis Calculator (S2SAC) is a tool specifically developed to improve the precision and dependability of statistical analyses in health research. S2SAC is a statistical software that can be easily used within the Microsoft Excel environment. It has a user-friendly interface and provides a wide range of statistical operations, such as outlier detection, normality testing, and both parametric and non-parametric tests. This application automates the intricate computations necessary for accurate sample size estimation and reliable statistical analysis, allowing researchers without substantial statistical experience to utilize advanced statistical approaches easily. This paper examines the potential of S2SAC through in-depth case studies, showcasing its efficacy in enhancing research design and safeguarding the credibility of research outcomes in the field of health sciences.

Keywords: Sample size estimation, Statistical analysis, Health sciences, S2SAC (Sample Size & Statistical Analysis Calculator), Statistical software

Medical Science, 2024, 28, e75ms3380

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DOI: https://doi.org/10.54905/disssi.v28i149.e75ms3380

Published: 16 July 2024