ABSTRACT
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.
TABLE OF CONTENTS
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chapter 4|19 pages
Formalities of the Age-Period-Cohort Analysis Conundrum and a Generalized Linear Mixed Models (GLMM) Framework
Size: 1.13 MB
chapter 5|49 pages
APC Accounting/Multiple Classification Model, Part I: Model Identification and Estimation Using the Intrinsic Estimator
Size: 0.58 MB
Size: 3.38 MB
chapter 7|40 pages
Mixed Effects Models: Hierarchical APC-Cross-Classified Random Effects Models (HAPC-CCREM), Part I: The Basics
Size: 0.45 MB
chapter 8|54 pages
Mixed Effects Models: Hierarchical APC-Cross-Classified Random Effects Models (HAPC-CCREM), Part II: Advanced Analyses
Size: 0.63 MB
chapter 9|27 pages
Mixed Effects Models: Hierarchical APC-Growth Curve Analysis of Prospective Cohort Data
Size: 0.32 MB
Size: 0.13 MB