Cohort Analysis

by

Yang Yang, Kenneth C. Land

• LAST REVIEWED: 29 November 2017
• LAST MODIFIED: 29 November 2017
• DOI: 10.1093/obo/9780199756384-0104

Introduction

Cohort analysis deals with the conceptualization, estimation, and interpretation of the differential contributions of three dimensions of temporal changes in phenomena of interest to demographers, epidemiologists, and social scientists. Researchers in these disciplines often deal with population or sample survey data in the form of observations or measurements on individuals or other units of analysis, such as groups/populations of individuals that are repeated or ordered temporally. The focus of interest is on the effects of the three temporal dimensions: (1) the ages of the individuals at the time of observation on an outcome of interest, termed age (A) effects, (2) the time periods of observation or measurement of the outcome, termed period (P) effects, and (3) the year of birth or some other shared life events for a set of individuals, termed cohort (C) effects. To address this problem, researchers compare age-specific data recorded at different points in time and from different cohorts. A systematic study of such data is termed age-period-cohort (APC) analysis. APC analysis has the unique ability to depict parsimoniously the entire complex of social, historical, and environmental factors that simultaneously affect individuals and populations of individuals. It has thus been widely used to address questions of enduring importance to studies of social change, aging, the etiology of diseases, and population processes and dynamics.

Reference Works

Relatively few books devoted solely to cohort analysis have been published; rather, most of the published works on this topic are peer-reviewed journal articles, entries in encyclopedias, or chapters in books. Mason and Fienberg 1985 is an edited volume containing fourteen chapters on conceptual and methodological approaches to APC (age-period-cohort) analysis and empirical applications thereof in demography and social research. It represents the state of the art of cohort analysis as of the mid-1980s. Glenn 2005 is a short monograph that reviews the APC literature in the social sciences up to the early 2000s and illustrates dilemmas in the identification and estimation of what will be described in this article as the age-period-cohort multiple classification/accounting model (see The Age-Period-Cohort Multiple Classification/Accounting Model). Smith 2008 is the introductory essay to a special issue of a research methods journal containing four articles on new approaches to the identification and estimation of APC models that go beyond the classic methods described in Mason and Fienberg 1985 and Glenn 2005. Yang and Land 2013 is a systematic exposition of a unifying generalized linear mixed models (GLMM) statistical modeling framework for APC analysis, associated estimation methods, and empirical applications of cohort analysis.

• Glenn, N. D. 2005. Cohort analysis. 2d ed. SAGE University Papers Series: Quantitative Applications in the Social Sciences. Thousand Oaks, CA: SAGE.

  DOI: 10.4135/9781412983662

  This monograph describes identification and estimation problems in the classical APC multiple classification/accounting model as studied in the period from 1973 to the early 2000s.

• Mason, W. M., and S. E. Fienberg, eds. 1985. Cohort analysis in social research: Beyond the identification problem. New York: Springer-Verlag.

  DOI: 10.1007/978-1-4613-8536-3

  An authoritative collection of articles on the conceptualization of cohort effects, problems of identification in APC models, and empirical APC analysis in the period from 1965 to 1985.

• Smith, H. L. 2008. Advances in age-period-cohort analysis: Introduction. In Special issue: Age–period–cohort models revisited. Sociological Methods & Research 36.3: 287–296.

  DOI: 10.1177/0049124107310636

  This article introduces a special issue of the journal on new approaches to APC analysis and places its four articles in the context of the broader literature on cohort analysis. Available online for purchase or by subscription.

• Yang, Y., and K. C. Land. 2013. Age-period-cohort analysis: New models, methods, and empirical applications. Chapman and Hall/CRC Interdisciplinary Statistics Series. Boca Raton, FL: Chapman and Hall.

  DOI: 10.1201/b13902

  Presents a unifying generalized linear mixed models (GLMM) statistical framework for APC analysis, expounds the associated methods, and describes several empirical applications.