Kim Jonghae, Kim Dong Hyuck, Kwak Sang Gyu
Department of Anesthesiology and Pain Medicine, Daegu Catholic University School of Medicine, Daegu, Korea.
Department of Medical Statistics, Daegu Catholic University School of Medicine, Daegu, Korea.
Korean J Anesthesiol. 2024 Oct;77(5):503-517. doi: 10.4097/kja.24016. Epub 2024 Aug 30.
The selection of statistical analysis methods in research is a critical and nuanced task that requires a scientific and rational approach. Aligning the chosen method with the specifics of the research design and hypothesis is paramount, as it can significantly impact the reliability and quality of the research outcomes.
This study explores a comprehensive guideline for systematically choosing appropriate statistical analysis methods, with a particular focus on the statistical hypothesis testing stage and categorization of variables. By providing a detailed examination of these aspects, this study aims to provide researchers with a solid foundation for informed methodological decision making. Moving beyond theoretical considerations, this study delves into the practical realm by examining the null and alternative hypotheses tailored to specific statistical methods of analysis. The dynamic relationship between these hypotheses and statistical methods is thoroughly explored, and a carefully crafted flowchart for selecting the statistical analysis method is proposed.
Based on the flowchart, we examined whether exemplary research papers appropriately used statistical methods that align with the variables chosen and hypotheses built for the research. This iterative process ensures the adaptability and relevance of this flowchart across diverse research contexts, contributing to both theoretical insights and tangible tools for methodological decision-making.
This study emphasizes the importance of a scientific and rational approach for the selection of statistical analysis methods. By providing comprehensive guidelines, insights into the null and alternative hypotheses, and a practical flowchart, this study aims to empower researchers and enhance the overall quality and reliability of scientific studies.
研究中统计分析方法的选择是一项关键且细致入微的任务，需要科学合理的方法。使所选方法与研究设计和假设的具体情况相匹配至关重要，因为这会对研究结果的可靠性和质量产生重大影响。
本研究探索了一套系统选择合适统计分析方法的综合指南，特别关注统计假设检验阶段和变量分类。通过对这些方面进行详细考察，本研究旨在为研究人员提供坚实基础，以便做出明智的方法学决策。超越理论考量，本研究通过考察针对特定统计分析方法量身定制的原假设和备择假设，深入到实际领域。对这些假设与统计方法之间的动态关系进行了全面探索，并提出了一个精心设计的统计分析方法选择流程图。
基于该流程图，我们检查了范例研究论文是否恰当地使用了与所选变量和为该研究构建的假设相一致的统计方法。这个迭代过程确保了该流程图在不同研究背景下的适应性和相关性，为理论见解和方法学决策的切实工具都做出了贡献。
本研究强调了科学合理地选择统计分析方法的重要性。通过提供全面的指南、对原假设和备择假设的见解以及一个实用的流程图，本研究旨在增强研究人员的能力，并提高科学研究的整体质量和可靠性。
