ABSTRACT
This chapter focuses on three research designs that allow analysts to distinguish age, period, and cohort effects and thus are more suitable for age-period-cohort (APC) analysis than cross-sectional or single-cohort panel designs. It identifies two to three prototypical datasets that characterize the application of APC analysis in each of three designs. In each case, the chapter commences with statements of substantive problems that arise from the scientific literature and then describes data that is analyzed to address these problems. It draws examples on a wide variety of topics and focuses on aging, longevity, and health disparities, as these are problems that have long histories of temporal analysis and for which APC analysis is highly salient. Cross-sectional data collected repeatedly across time, however, are well suited for APC analysis. The chapter focuses on the possibilities for APC analysis using repeated cross-sectional data at the population level.
