{"title":"生存分析:引物","authors":"Arun Valsan, KuttyNarayanan Anila, Sivaprasadan Saraswathy, Surendran Sudhindran","doi":"10.4103/amjm.amjm_60_23","DOIUrl":null,"url":null,"abstract":"Survival analysis is an important time-bound statistical tool used in medical research to gather valuable insights into outcomes, treatment efficacy, and disease progression. This tool employs various models to run the data such as Cox proportional hazards ratio, life tables, Kaplan–Meier estimates among others. This write-up highlights various survival analysis techniques that are used to estimate time to event in research. This article provides insights into the general concepts and a few important tools of survival analytics to the readers.","PeriodicalId":138060,"journal":{"name":"Amrita Journal of Medicine","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Survival analysis: A primer\",\"authors\":\"Arun Valsan, KuttyNarayanan Anila, Sivaprasadan Saraswathy, Surendran Sudhindran\",\"doi\":\"10.4103/amjm.amjm_60_23\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Survival analysis is an important time-bound statistical tool used in medical research to gather valuable insights into outcomes, treatment efficacy, and disease progression. This tool employs various models to run the data such as Cox proportional hazards ratio, life tables, Kaplan–Meier estimates among others. This write-up highlights various survival analysis techniques that are used to estimate time to event in research. This article provides insights into the general concepts and a few important tools of survival analytics to the readers.\",\"PeriodicalId\":138060,\"journal\":{\"name\":\"Amrita Journal of Medicine\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Amrita Journal of Medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4103/amjm.amjm_60_23\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Amrita Journal of Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4103/amjm.amjm_60_23","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Survival analysis is an important time-bound statistical tool used in medical research to gather valuable insights into outcomes, treatment efficacy, and disease progression. This tool employs various models to run the data such as Cox proportional hazards ratio, life tables, Kaplan–Meier estimates among others. This write-up highlights various survival analysis techniques that are used to estimate time to event in research. This article provides insights into the general concepts and a few important tools of survival analytics to the readers.
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