Statistical corner: Using R to build, analyse and plot clinical neurological datasets

Mikko J. Pyysalo, Teemu Vesterinen
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Abstract

Introduction: In the field of medical research, large volumes of data need to be analysed accurately, and it is crucial to pre-process the data before it can be analysed. The 'R' environment is a programming language and environment for statistical computing and graphics suitable for the analysis of data sets. Objectives: To provide examples on how to utilise the R language for data processing, and its usefulness for medical researchers. Materials and Methods: Two real world datasets, ie, data for: 'Effect of Morning Blood Pressure Peak on Early Progressive Ischemic Stroke: A Prospective Clinical Study' and data for: 'Impact of early surgery of ruptured cerebral aneurysms on vasospasm and hydrocephalus after SAH: our preliminary series' have been used to present an example for two different approaches for the process of data analysis using R. Results: Accurate and tidy data sets were obtained. Conclusions: R is a reliable environment for the processing of large data sets.
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统计角:使用R构建,分析和绘制临床神经学数据集
导读:在医学研究领域,需要对大量的数据进行准确的分析,在分析数据之前对数据进行预处理是至关重要的。R环境是一种用于统计计算和图形的编程语言和环境,适用于数据集的分析。目的:提供如何使用R语言进行数据处理的示例,以及它对医学研究人员的有用性。材料和方法:两个真实世界的数据集,即数据:“早晨血压峰值对早期进展性缺血性卒中的影响:一项前瞻性临床研究”和数据:“破裂的脑动脉瘤早期手术对SAH后血管痉挛和脑积水的影响:我们的初步系列”,以两种不同的方法为例,使用r进行数据分析过程。结果:获得了准确而有序的数据集。结论:R是处理大型数据集的可靠环境。
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