ABSTRACT

Age, Period and Cohort Effects: Statistical Analysis and the Identification Problem gives a number of perspectives from top methodologists and applied researchers on the best ways to attempt to answer Age–Period–Cohort related questions about society.

Age–Period–Cohort (APC) analysis is a fundamental topic for any quantitative social scientist studying individuals over time. At the same time, it is also one of the most misunderstood and underestimated topics in quantitative methods. As such, this book is key reference material for researchers wanting to know how to deal with APC issues appropriately in their statistical modelling. It deals with the identification problem caused by the co-linearity of the three variables, considers why some currently used methods are problematic and suggests ideas for what applied researchers interested in APC analysis should do.

Whilst the perspectives are varied, the book provides a unified view of the subject in a reader-friendly way that will be accessible to social scientists with a moderate level of quantitative understanding, across the social and health sciences.

chapter 4|29 pages

The Lexis surface

A tool and workflow for better reasoning about population data

chapter 6|33 pages

Learning from age–period–cohort data

Bounds, mechanisms, and 2D-APC graphs

chapter 7|25 pages

Modeling factors affecting age, period and cohort trends

The effect of cigarette smoking on lung cancer trends

chapter 9|30 pages

Age–period–cohort analysis

What is it good for?