{"title":"GRAPHICAL APPROACH TO AGE-PERIOD-COHORT ANALYSIS","authors":"A. Sagan","doi":"10.22630/aspe.2021.20.2.17","DOIUrl":null,"url":null,"abstract":"The paper presents the graphical approach to decomposition of APC effect in cohort studies (mainly applied to demographic phenomena) using multilevel or accelerated longitudinal design. The aim of the paper is to present and visualize the pure age, period and cohort effects based on simulated data with an increment of five for each successive age, period and cohort variation. In cohort analysis on real data all of the effects are usually interrelated. The analysis shows basic patterns of two-variate APC decomposition (age within period, age within cohort, cohort within period, period within age, cohort within age, period within cohort) and reveals the trajectory of curves for each of the pure effects. The APC plots are developed using apc library of R package.","PeriodicalId":34287,"journal":{"name":"Acta Scientiarum Polonorum Oeconomia","volume":"118 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Scientiarum Polonorum Oeconomia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22630/aspe.2021.20.2.17","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
The paper presents the graphical approach to decomposition of APC effect in cohort studies (mainly applied to demographic phenomena) using multilevel or accelerated longitudinal design. The aim of the paper is to present and visualize the pure age, period and cohort effects based on simulated data with an increment of five for each successive age, period and cohort variation. In cohort analysis on real data all of the effects are usually interrelated. The analysis shows basic patterns of two-variate APC decomposition (age within period, age within cohort, cohort within period, period within age, cohort within age, period within cohort) and reveals the trajectory of curves for each of the pure effects. The APC plots are developed using apc library of R package.