Age-period-cohort models : approaches and analyses with aggregate data

Introduction to the Age, Period, and Cohort Mix Introduction Interest in Age, Period, and Cohort Importance of Cohorts Plan for the Book Multiple Classification Models and Constrained Regression Introduction Linearly Coded Age-Period-Cohort (APC) Model Categorically Coded APC Model Generalized Linear Models Null Vector Model Fit Solution Is Orthogonal to the Constraint Examining the Relationship between Solutions Differences between Constrained Solutions as Rotations of Solutions Solutions Ignoring One or More of the Age, Period, or Cohort Factors Bias: Constrained Estimates and the Data Generating Parameters Unbiased Estimation under a Constraint A Plausible Constraint with Some Extra Empirical Support Geometry of APC Models and Constrained Estimation Introduction General Geometric View of Rank Deficient by One Models Generalization to Systems with More Dimensions APC Model with Linearly Coded Variables Equivalence of the Geometric and Algebraic Solutions Geometry of the Multiple Classification Model Distance from Origin and Distance along the Line of Solutions Empirical Example: Frost's Tuberculosis Data Summarizing Some Important Features from the Geometry of APC Models Problem with Mechanical Constraints Estimable Functions Approach Introduction Estimable Functions l'sv Approach for Establishing Estimable Functions in APC Models Some Examples of Estimable Functions Derived Using the l'sv Approach Comments on the l'sv Approach Estimable Functions with Empirical Data More Substantive Examination of Differences of Male and Female Lung Cancer Mortality Rates Partitioning the Variance in APC Models Introduction Age-Period-Cohort Analysis of Variance (APC ANOVA) Approach to Attributing Variance APC Mixed Model Hierarchical APC Model Empirical Example Using Homicide Offending Data Factor-Characteristic Approach Introduction Characteristics for One Factor Characteristics for Two or More Factors Variance Decomposition for Factors and for Factor Characteristics Empirical Examples: Age-Period-Specific Suicide Rates and Frequencies Age-Period-Cohort Characteristics (APCC) Analysis of Suicide Data with Two Cohort Characteristics Age-Cohort-Period Characteristics (ACPC) Analysis of the Suicide Data with Two Period Characteristics Age-Period-Characteristics-Cohort Characteristics Model Approaches Based on Factor Characteristics and Mechanism Additional Features and Analyses of Factor-Characteristic Models Conclusions: An Empirical Example Introduction Empirical Example: Homicide Offending Index Conclusions and References appear at the end of each chapter.