{"title":"统计角:使用R构建,分析和绘制临床神经学数据集","authors":"Mikko J. Pyysalo, Teemu Vesterinen","doi":"10.4103/jcvs.jcvs_29_20","DOIUrl":null,"url":null,"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.","PeriodicalId":218723,"journal":{"name":"Journal of Cerebrovascular Sciences","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Statistical corner: Using R to build, analyse and plot clinical neurological datasets\",\"authors\":\"Mikko J. Pyysalo, Teemu Vesterinen\",\"doi\":\"10.4103/jcvs.jcvs_29_20\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":218723,\"journal\":{\"name\":\"Journal of Cerebrovascular Sciences\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Cerebrovascular Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4103/jcvs.jcvs_29_20\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cerebrovascular Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4103/jcvs.jcvs_29_20","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Statistical corner: Using R to build, analyse and plot clinical neurological datasets
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.