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Age, Period and Cohort Effects: Statistical Analysis and the Identification Problem de Andrew Bell

Age, Period and Cohort Effects: Statistical Analysis and the Identification Problem

Editat de Andrew Bell
en Limba Engleză Paperback – 6 noi 2020

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.

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Specificații

ISBN-13: 9780367174439
ISBN-10: 036717443X
Pagini: 248
Ilustrații: 38 Line drawings, black and white; 32 Halftones, black and white; 13 Tables, black and white; 70 Illustrations, black and white
Dimensiuni: 156 x 234 x 17 mm
Greutate: 0.45 kg
Ediția:1
Editura: Taylor & Francis
Colecția Routledge
Locul publicării:Oxford, United Kingdom

Public țintă

Postgraduate and Professional

Cuprins

Chapter 1. Introduction to Age, Period and Cohort Effects  Chapter 2. The Pros and Cons of Constraining Variables  Chapter 3. Multilevel Models for Age-Period-Cohort Analysis  Chapter 4. The Lexis Surface: A Tool and Workflow for Better Reasoning about Population Data  Chapter 5. Detecting the ‘Black Hole’ of Age-Period Excess Mortality in 25 Countries: Age-Period-Cohort Residual Analysis  Chapter 6. Learning from Age-Period-Cohort Data: Bounds, Mechanisms, and 2D-APC Graphs  Chapter 7. Assessing Factors that Contribute to Age, Period and Cohort Trends  Chapter 8. Bayesian Age-Period-Cohort Models  Chapter 9. Age-Period-Cohort Analysis: What is it Good For?  Chapter 10. The Line of Solutions and Understanding Age-Period-Cohort Models

Notă biografică

Andrew Bell is a senior lecturer in Quantitative Social Sciences at the Sheffield Methods Institute, University of Sheffield, UK.

Recenzii

"The interplay of lifecycle, history and generation - or age, period and cohort, in humbler terms – is one of the great puzzles in the study of individual and social change. This landmark collection is a major contribution on a topic that reaches from philosophy to social statistics. Don’t be overtaken by time: start reading now!" – Professor David Voas, University College London, UK
"Understanding age, period, and cohort effects is a mainstream concern in all the social sciences. But researchers have struggled with how exactly to approach "APC" issues. This book provides invaluable, up-to-date methodological guidance" – Professor Malcolm Fairbrother, Umeå University, Sweden

Descriere

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.