Age, Period and Cohort Effects

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advanced age-period-cohort statistical techniques
Age
Age Cohort Model
Age Linear Effect
Age Nonlinear
Age Period Cohort Analysis
Age Period Cohort Effects
Age Period Cohort Model
Age Slope
Aid Mortality
APC analysis
APC Model
Bayesian inference methods
Birth Cohort
Carcinogenesis Model
Category=GPS
Category=JMB
Category=PBT
Cohort Effects
Cohort Elements
Cohort Residuals
Cohort Trend
Constraning variables
demographic modelling
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
Estimable Functions
Identification problem
Informal Models
Intrinsic Estimator
Lee Carter Model
Lexis diagram analysis
Lexis surfaces
Linear Effects
Linear Trend
Lung Cancer Mortality
multilevel modelling
period and cohort effects
population trend analysis
Posterior Distribution
Quantitative methods
quantitative social research
Quantitative social scientist
Statistical analysis
Statistical modelling
Statistics
Underlying Population Structure
Unidentified Parameter

Product details

  • ISBN 9780367174422
  • Weight: 620g
  • Dimensions: 156 x 234mm
  • Publication Date: 06 Nov 2020
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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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.

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