Age-Period-Cohort Analysis
New Models, Methods, and Empirical Applications
Published on 19. April 2016
352 pages
978-1-000-21873-2 (ISBN)
Description
This book explores the ways in which statistical models, methods, and research designs can be used to open new possibilities for APC analysis. Within a single, consistent HAPC-GLMM statistical modeling framework, the authors synthesize APC models and methods for three research designs: age-by-time period tables of population rates or proportions, repeated cross-section sample surveys, and accelerated longitudinal panel studies. They show how the empirical application of the models to various problems leads to many fascinating findings on how outcome variables develop along the age, period, and cohort dimensions.
Reviews / Votes
" ... presents all the important background and new developments in one place, with examples and software for easy applications. I would recommendthis book to anyone working in various research disciplines that rely on APC analysis."-Journal of the American Statistical Association
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
File size
23,73 MB
ISBN-13
978-1-000-21873-2 (9781000218732)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Yang Yang | Kenneth C. Land
Age-Period-Cohort Analysis
New Models, Methods, and Empirical Applications
Book
01/2023
1st Edition
Chapman & Hall/CRC
€80.75
Shipment within 10-20 days
Yang Yang | Kenneth C. Land
Age-Period-Cohort Analysis
New Models, Methods, and Empirical Applications
Book
02/2013
1st Edition
CRC Press
€171.70
Shipment within 15-20 days
Persons
Yang Yang is an associate professor in the Department of Sociology and Lineberger Comprehensive Cancer Center and a faculty fellow in the Carolina Population Center at the University of North Carolina-Chapel Hill. Dr. Yang's research encompasses the areas of demography, medical sociology, cancer, and quantitative methodology. Her work has been featured in numerous media outlets, including the American Sociological Review, CNN, Associated Press, Reuters, Washington Post, and Chicago Tribune. She received a Ph.D. in sociology from Duke University.
Kenneth C. Land is a John Franklin Crowell professor of sociology and faculty director of the Center for Population Health and Aging at Duke University. Dr. Land is a fellow of the American Statistical Association, the Sociological Research Association, the American Association for the Advancement of Science, the International Society for Quality-of-Life Studies, and the American Society of Criminology. His research focuses on contemporary social trends and quality-of-life measurement, social problems, demography, criminology, organizations, and mathematical and statistical models and methods for the study of social and demographic processes. He received a Ph.D. in sociology and mathematics from the University of Texas at Austin.
Kenneth C. Land is a John Franklin Crowell professor of sociology and faculty director of the Center for Population Health and Aging at Duke University. Dr. Land is a fellow of the American Statistical Association, the Sociological Research Association, the American Association for the Advancement of Science, the International Society for Quality-of-Life Studies, and the American Society of Criminology. His research focuses on contemporary social trends and quality-of-life measurement, social problems, demography, criminology, organizations, and mathematical and statistical models and methods for the study of social and demographic processes. He received a Ph.D. in sociology and mathematics from the University of Texas at Austin.
Content
Introduction. Why Cohort Analysis? APC Analysis of Data from Three Common Research Designs. Formalities of the Age-Period-Cohort Analysis Conundrum and a Generalized Linear Mixed Models (GLMM) Framework. APC Accounting/Multiple Classification Model, Part I: Model Identification and Estimation Using the Intrinsic Estimator. APC Accounting/Multiple Classification Model, Part II: Empirical Applications. Mixed Effects Models: Hierarchical APC-Cross-Classified Random Effects Models (HAPC-CCREM), Part I: The Basics. Mixed Effects Models: Hierarchical APC-Cross-Classified Random Effects Models (HAPC-CCREM), Part II: Advanced Analyses. Mixed Effects Models: Hierarchical APC-Growth Curve Analysis of Prospective Cohort Data. Directions for Future Research and Conclusion. Index.
