Software Application Profile: CaseCohortCoxSurvival-an R package for case-cohort inference for relative hazard and pure risk under the Cox model.

IF 6.4 2区医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

International journal of epidemiology Pub Date : 2025-02-16 DOI:10.1093/ije/dyaf016

Lola Etiévant, Mitchell H Gail

{"title":"Software Application Profile: CaseCohortCoxSurvival-an R package for case-cohort inference for relative hazard and pure risk under the Cox model.","authors":"Lola Etiévant, Mitchell H Gail","doi":"10.1093/ije/dyaf016","DOIUrl":null,"url":null,"abstract":"Motivation: The case-cohort design only requires covariate measurements for individuals experiencing the outcome of interest (cases) and individuals in a subcohort randomly selected from the cohort. Stratified subcohort sampling and calibration of the design weights increase efficiency of relative hazard and pure risk estimates, but require specifically adapted variance estimators. Yet, the 'robust' variance formula is often inappropriately used with stratified case-cohort data. Also, weight calibration and pure risk estimation are underused, possibly because of the lack of convenient software.Implementation: An influence-based method for inference of case-cohort Cox model relative hazards and pure risks is implemented in the CaseCohortCoxSurvival R package.General features: CaseCohortCoxSurvival allows estimation of parameter and variance of Cox model relative hazards and pure risks from case-cohort data. It can handle stratified subcohort sampling and calibrate the design weights. Both features are properly accounted for in the variance estimation.Availability: CaseCohortCoxSurvival is available on the Comprehensive R Archive Network at [https://cran.r-project.org/package=CaseCohortCoxSurvival].","PeriodicalId":14147,"journal":{"name":"International journal of epidemiology","volume":"54 2","pages":""},"PeriodicalIF":6.4000,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11882301/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of epidemiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/ije/dyaf016","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}

引用次数: 0

Abstract

Motivation: The case-cohort design only requires covariate measurements for individuals experiencing the outcome of interest (cases) and individuals in a subcohort randomly selected from the cohort. Stratified subcohort sampling and calibration of the design weights increase efficiency of relative hazard and pure risk estimates, but require specifically adapted variance estimators. Yet, the 'robust' variance formula is often inappropriately used with stratified case-cohort data. Also, weight calibration and pure risk estimation are underused, possibly because of the lack of convenient software.

Implementation: An influence-based method for inference of case-cohort Cox model relative hazards and pure risks is implemented in the CaseCohortCoxSurvival R package.

General features: CaseCohortCoxSurvival allows estimation of parameter and variance of Cox model relative hazards and pure risks from case-cohort data. It can handle stratified subcohort sampling and calibrate the design weights. Both features are properly accounted for in the variance estimation.

Availability: CaseCohortCoxSurvival is available on the Comprehensive R Archive Network at [https://cran.r-project.org/package=CaseCohortCoxSurvival].

查看原文本刊更多论文

软件应用简介：casecohortcoxsurvival -一个在Cox模型下对相对风险和纯风险进行病例队列推断的R软件包。

动机：病例队列设计只需要对经历感兴趣结果（病例）的个体和从队列中随机选择的亚队列中的个体进行协变量测量。分层亚队列抽样和设计权重的校准提高了相对危险和纯风险估计的效率，但需要特别适应方差估计。然而，“稳健”方差公式通常不适当地用于分层病例队列数据。此外，可能由于缺乏方便的软件，权重校准和纯粹的风险估计没有得到充分利用。实现：在CaseCohortCoxSurvival R包中实现了一种基于影响的方法来推断病例队列Cox模型的相对风险和纯风险。一般特征：CaseCohortCoxSurvival允许从病例队列数据中估计Cox模型相对风险和纯风险的参数和方差。它可以处理分层次队列抽样和校准设计权重。这两个特征在方差估计中都得到了适当的考虑。可用性：CaseCohortCoxSurvival可在综合R档案网络上获得[https://cran.r-project.org/package=CaseCohortCoxSurvival]]。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

International journal of epidemiology 医学-公共卫生、环境卫生与职业卫生

CiteScore

13.60

自引率

2.60%

发文量

226

审稿时长

3 months

期刊介绍： The International Journal of Epidemiology is a vital resource for individuals seeking to stay updated on the latest advancements and emerging trends in the field of epidemiology worldwide. The journal fosters communication among researchers, educators, and practitioners involved in the study, teaching, and application of epidemiology pertaining to both communicable and non-communicable diseases. It also includes research on health services and medical care. Furthermore, the journal presents new methodologies in epidemiology and statistics, catering to professionals working in social and preventive medicine. Published six times a year, the International Journal of Epidemiology provides a comprehensive platform for the analysis of data. Overall, this journal is an indispensable tool for staying informed and connected within the dynamic realm of epidemiology.