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
This article considers the effects of age, period, and cohort in social studies and chronic disease ...
In studying temporally ordered rates of events, epidemiologists, demographers, and social scientists...
Cancer remains the second leading cause of death in the U.S. and worldwide. To thoroughly understand...
Age-Period-Cohort Analysis: New Models, Methods, and Empirical Applications is based on a decade of ...
Age\u2013period\u2013cohort (APC) analyses are a family of statistical techniques to study temporal ...
Context: Age, period and birth cohort (APC) effects have been known for decades in biological, healt...
Age–period–cohort models provide a useful method for modeling incidence and mortality rates. It is w...
BackgroundAge-period-cohort (APC) models are often used to decompose health trends into period- and ...
Age, Period, and Cohort (APC) models have been applied to analyze disease incidence or mortality rat...
This paper develops a design-based approach to identifying cohort effects in APC analyses. Cohort ef...
Social scientists have recognized the importance of age-period-cohort (APC) models for half a centur...
Standard descriptive methods for the analysis of cancer surveillance data include canonical plots ba...
The apc package includes functions for age-period-cohort analysis based on the canonical parametrisa...
Age-period-cohort models have been used to examine and forecast cancer incidence and mortality for o...
Multilevel models (aka mixed models, random effects models, hierarchical linear models) have been us...
This article considers the effects of age, period, and cohort in social studies and chronic disease ...
In studying temporally ordered rates of events, epidemiologists, demographers, and social scientists...
Cancer remains the second leading cause of death in the U.S. and worldwide. To thoroughly understand...
Age-Period-Cohort Analysis: New Models, Methods, and Empirical Applications is based on a decade of ...
Age\u2013period\u2013cohort (APC) analyses are a family of statistical techniques to study temporal ...
Context: Age, period and birth cohort (APC) effects have been known for decades in biological, healt...
Age–period–cohort models provide a useful method for modeling incidence and mortality rates. It is w...
BackgroundAge-period-cohort (APC) models are often used to decompose health trends into period- and ...
Age, Period, and Cohort (APC) models have been applied to analyze disease incidence or mortality rat...
This paper develops a design-based approach to identifying cohort effects in APC analyses. Cohort ef...
Social scientists have recognized the importance of age-period-cohort (APC) models for half a centur...
Standard descriptive methods for the analysis of cancer surveillance data include canonical plots ba...
The apc package includes functions for age-period-cohort analysis based on the canonical parametrisa...
Age-period-cohort models have been used to examine and forecast cancer incidence and mortality for o...
Multilevel models (aka mixed models, random effects models, hierarchical linear models) have been us...
This article considers the effects of age, period, and cohort in social studies and chronic disease ...
In studying temporally ordered rates of events, epidemiologists, demographers, and social scientists...
Cancer remains the second leading cause of death in the U.S. and worldwide. To thoroughly understand...