{"title":"Methods for stratification of person-time and events - a prerequisite for Poisson regression and SIR estimation.","authors":"Klaus Rostgaard","doi":"10.1186/1742-5573-5-7","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Many epidemiological methods for analysing follow-up studies require the calculation of rates based on accumulating person-time and events, stratified by various factors. Managing this stratification and accumulation is often the most difficult aspect of this type of analysis.</p><p><strong>Tutorial: </strong>We provide a tutorial on accumulating person-time and events, stratified by various factors i.e. creating event-time tables. We show how to efficiently generate event-time tables for many different outcomes simultaneously. We also provide a new vocabulary to characterise and differentiate time-varying factors. The tutorial is focused on using a SAS macro to perform most of the common tasks in the creation of event-time tables. All the most common types of time-varying covariates can be generated and categorised by the macro. It can also provide output suitable for other types of survival analysis (e.g. Cox regression). The aim of our methodology is to support the creation of bug-free, readable, efficient, capable and easily modified programs for making event-time tables. We briefly compare analyses based on event-time tables with Cox regression and nested case-control studies for the analysis of follow-up data.</p><p><strong>Conclusion: </strong>Anyone working with time-varying covariates, particularly from large detailed person-time data sets, would gain from having these methods in their programming toolkit.</p>","PeriodicalId":87082,"journal":{"name":"Epidemiologic perspectives & innovations : EP+I","volume":"5 ","pages":"7"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2615420/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Epidemiologic perspectives & innovations : EP+I","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/1742-5573-5-7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: Many epidemiological methods for analysing follow-up studies require the calculation of rates based on accumulating person-time and events, stratified by various factors. Managing this stratification and accumulation is often the most difficult aspect of this type of analysis.
Tutorial: We provide a tutorial on accumulating person-time and events, stratified by various factors i.e. creating event-time tables. We show how to efficiently generate event-time tables for many different outcomes simultaneously. We also provide a new vocabulary to characterise and differentiate time-varying factors. The tutorial is focused on using a SAS macro to perform most of the common tasks in the creation of event-time tables. All the most common types of time-varying covariates can be generated and categorised by the macro. It can also provide output suitable for other types of survival analysis (e.g. Cox regression). The aim of our methodology is to support the creation of bug-free, readable, efficient, capable and easily modified programs for making event-time tables. We briefly compare analyses based on event-time tables with Cox regression and nested case-control studies for the analysis of follow-up data.
Conclusion: Anyone working with time-varying covariates, particularly from large detailed person-time data sets, would gain from having these methods in their programming toolkit.