Indrayan A
Department of Clinical Research, Max Healthcare, New Delhi, India.
J Postgrad Med. 2025 Jan 1;71(1):41-44. doi: 10.4103/jpgm.jpgm_755_24. Epub 2025 Mar 6.
Data are the soul of most empirical research. Adequate data collection and their proper collation are essential to arrive at right conclusions. These conclusions are mostly drawn from the statistical analysis of properly collated data. Since the methods of statistical analysis are different for different types of data, a clear understanding of various types of data is necessary for their efficient processing. Whereas broad types of data-quantitative and qualitative-are well known, some researchers struggle with the proper collation of ordinal data and quantitative categories. Additionally, some young researchers need guidance on preparing tables to communicate their results effectively. Graphics add muscles to the skeleton of data and need to be judiciously chosen. This article provides details of various types of data, their adequacy, and their proper collation, including a brief on tables and graphics. Almost all medical researchers carry out these activities - thus, this may have wide ramifications. Although this article primarily targets postgraduate students and young researchers, our interaction with a diverse group of researchers suggests that many experienced researchers may also find this article useful in the management of their data for reaching the right conclusions.
数据是大多数实证研究的核心。充分的数据收集及其恰当整理对于得出正确结论至关重要。这些结论大多源于对恰当整理后的数据进行的统计分析。由于针对不同类型的数据,统计分析方法各异,因此要高效处理数据,就必须清楚了解各类数据。虽然广泛的数据类型——定量数据和定性数据——广为人知,但一些研究人员在对有序数据和定量类别进行恰当整理时仍存在困难。此外,一些年轻研究人员在准备表格以有效传达研究结果方面需要指导。图表为数据框架增添了力量,需要谨慎选择。本文详细介绍了各类数据、其充分性以及恰当的整理方法,包括对表格和图表的简要说明。几乎所有医学研究人员都会进行这些活动——因此,这可能会产生广泛影响。尽管本文主要面向研究生和年轻研究人员,但我们与不同研究人员群体的交流表明,许多经验丰富的研究人员可能也会发现本文在管理数据以得出正确结论方面很有用。