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Age-period-cohort analysis : new models, methods, and empirical applications / Yang Yang and Kenneth C. Land.

By: Yang, Yang, 1975 [author.]Contributor(s): Land, Kenneth CMaterial type: TextTextSeries: Interdisciplinary statisticsPublisher: Boca Raton, Fla. : CRC Press, 2013Description: 1 online resource (xiii, 338 pages)ISBN: 9780429096204Subject(s): Age groups -- Statistical methods | Cohort analysisAdditional physical formats: Print version: : No titleDDC classification: 001.422 LOC classification: HB849.47 | .Y36 2013Online access: Click here to view.
Contents:
1. Introduction 2. Why cohort analysis? 3. APC analysis of data from three common research designs 4. Formalities of the age-period-cohort analysis conundrum and a generalized linear mixed models (GLMM) framework 5. APC accounting/multiple classification model, part I : model identification and estimation using the intrinsic estimator 6. APC accounting/multiple classification model, part II : empirical applications 7. Mixed effects models : hierarchical APC-cross-classified random effects models (HAPC-CCREM), part I : the basics 8. Mixed effects models : hierarchical APC-cross-classified random effects models (HAPC-CCREM), part II : advanced analyses 9. Mixed effects models : hierarchical APC-growth curve analysis of prospective cohort data 10. Directions for future research and conclusion.
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A Chapman & Hall book.

1. Introduction 2. Why cohort analysis? 3. APC analysis of data from three common research designs 4. Formalities of the age-period-cohort analysis conundrum and a generalized linear mixed models (GLMM) framework 5. APC accounting/multiple classification model, part I : model identification and estimation using the intrinsic estimator 6. APC accounting/multiple classification model, part II : empirical applications 7. Mixed effects models : hierarchical APC-cross-classified random effects models (HAPC-CCREM), part I : the basics 8. Mixed effects models : hierarchical APC-cross-classified random effects models (HAPC-CCREM), part II : advanced analyses 9. Mixed effects models : hierarchical APC-growth curve analysis of prospective cohort data 10. Directions for future research and conclusion.

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