{"title":"[将连续变量二分时统计能力的巨大损失]。","authors":"C Carazo-Díaz, L Prieto-Valiente","doi":"10.33588/rn.7801.2023163","DOIUrl":null,"url":null,"abstract":"<p><p>A very common practice in medical research, during the process of data analysis, is to dichotomise numerical variables in two groups. This leads to the loss of very useful information that can undermine the effectiveness of the research. Several examples are used to show how the dichotomisation of numerical variables can lead to a loss of statistical power in studies. This can be a critical aspect in assessing, for example, whether a therapeutic procedure is more effective or whether a certain factor is a risk factor. Dichotomising continuous variables is therefore not recommended unless there is a very specific reason to do so.</p>","PeriodicalId":21281,"journal":{"name":"Revista de neurologia","volume":"78 1","pages":"27-29"},"PeriodicalIF":0.8000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11064942/pdf/","citationCount":"0","resultStr":"{\"title\":\"[The dramatic loss of statistical power when dichotomising continuous variables].\",\"authors\":\"C Carazo-Díaz, L Prieto-Valiente\",\"doi\":\"10.33588/rn.7801.2023163\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>A very common practice in medical research, during the process of data analysis, is to dichotomise numerical variables in two groups. This leads to the loss of very useful information that can undermine the effectiveness of the research. Several examples are used to show how the dichotomisation of numerical variables can lead to a loss of statistical power in studies. This can be a critical aspect in assessing, for example, whether a therapeutic procedure is more effective or whether a certain factor is a risk factor. Dichotomising continuous variables is therefore not recommended unless there is a very specific reason to do so.</p>\",\"PeriodicalId\":21281,\"journal\":{\"name\":\"Revista de neurologia\",\"volume\":\"78 1\",\"pages\":\"27-29\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11064942/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Revista de neurologia\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.33588/rn.7801.2023163\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista de neurologia","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.33588/rn.7801.2023163","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
[The dramatic loss of statistical power when dichotomising continuous variables].
A very common practice in medical research, during the process of data analysis, is to dichotomise numerical variables in two groups. This leads to the loss of very useful information that can undermine the effectiveness of the research. Several examples are used to show how the dichotomisation of numerical variables can lead to a loss of statistical power in studies. This can be a critical aspect in assessing, for example, whether a therapeutic procedure is more effective or whether a certain factor is a risk factor. Dichotomising continuous variables is therefore not recommended unless there is a very specific reason to do so.