{"title":"Estimating and displaying population attributable fractions using the R package: graphPAF.","authors":"John Ferguson, Maurice O'Connell","doi":"10.1007/s10654-024-01129-1","DOIUrl":null,"url":null,"abstract":"<p><p>Here we introduce graphPAF, a comprehensive R package designed for estimation, inference and display of population attributable fractions (PAF) and impact fractions. In addition to allowing inference for standard population attributable fractions and impact fractions, graphPAF facilitates display of attributable fractions over multiple risk factors using fan-plots and nomograms, calculations of attributable fractions for continuous exposures, inference for attributable fractions appropriate for specific risk factor <math><mo>→</mo></math> mediator <math><mo>→</mo></math> outcome pathways (pathway-specific attributable fractions) and Bayesian network-based calculations and inference for joint, sequential and average population attributable fractions in multi-risk factor scenarios. This article can be used as both a guide to the theory of attributable fraction estimation and a tutorial regarding how to use graphPAF in practical examples.</p>","PeriodicalId":11907,"journal":{"name":"European Journal of Epidemiology","volume":" ","pages":"715-742"},"PeriodicalIF":7.7000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11343908/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Epidemiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10654-024-01129-1","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/6 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
Abstract
Here we introduce graphPAF, a comprehensive R package designed for estimation, inference and display of population attributable fractions (PAF) and impact fractions. In addition to allowing inference for standard population attributable fractions and impact fractions, graphPAF facilitates display of attributable fractions over multiple risk factors using fan-plots and nomograms, calculations of attributable fractions for continuous exposures, inference for attributable fractions appropriate for specific risk factor mediator outcome pathways (pathway-specific attributable fractions) and Bayesian network-based calculations and inference for joint, sequential and average population attributable fractions in multi-risk factor scenarios. This article can be used as both a guide to the theory of attributable fraction estimation and a tutorial regarding how to use graphPAF in practical examples.
期刊介绍：
The European Journal of Epidemiology, established in 1985, is a peer-reviewed publication that provides a platform for discussions on epidemiology in its broadest sense. It covers various aspects of epidemiologic research and statistical methods. The journal facilitates communication between researchers, educators, and practitioners in epidemiology, including those in clinical and community medicine. Contributions from diverse fields such as public health, preventive medicine, clinical medicine, health economics, and computational biology and data science, in relation to health and disease, are encouraged. While accepting submissions from all over the world, the journal particularly emphasizes European topics relevant to epidemiology. The published articles consist of empirical research findings, developments in methodology, and opinion pieces.
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