This book provides theoretical and applied material for estimating vital parts of demography and health issues including the healthy aging process along with calculating the healthy life years lost to disability. It further includes the appropriate methodology for the optimum health expenditure allocation. Through providing data analysis, statistical and stochastic methodology, probability approach and important applications, the book explores topics such as aging and mortality, birth-death processes, self-perceived age, life-time and survival as well as pension and labor-force. By providing a methodological approach to health problems in demography and society including and quantifying important parameters, this book is a valuable guide for researchers, theoreticians and practitioners from various disciplines.
Cuprins
Part I: Healthy Aging, Healthy Life Years Lost and Health Expenditure Allocation.- Chapter 1. Relation of the Weibull Shape Parameter with the Healthy Life Years Lost Estimates: Analytic Derivation and Estimation from an Extended Life Table.- Chapter 2. Direct Healthy Life Expectancy Estimates from Life Tables with a Sullivan Extension. Bridging the Gap Between HALE and Eurostat Estimates.- Chapter 3. Modeling the Health Expenditure in Japan, 2011. A Healthy Life Years Lost Methodology.- Chapter 4. Healthy Ageing in Czechia.- Chapter 5. Evolution of Systems with Power-Law Memory: Do We Have to Die?.- Part II: Mortality Modeling and Applications.- Chapter 6. Structural Equation Modeling: Infant Mortality Rate in Egypt Application.- Chapter 7. Modeling of mortality in elderly by lung cancer in the Northeast of Brazil.- Chapter 8. Demographics of the Russian pension reform.- Chapter 9. Using the Developing Countries Mortality Database (DCMD) to Probabilistically Evaluate the Completeness of Death Registration at Old Ages.- Chapter 10. Mortality developments in Greece from the cohort perspective.- Chapter 11. On demographic approach of the BGGM distribution parameters on Italy and Sweden.- Chapter 12. Alcohol consumption in selected European countries.- Part III: Birth-Death Process, Self-perceived Age and Gender Differences.- Chapter 13. Modelling monthly birth and deaths using Seasonal Forecasting Methods as an input for population estimates.- Chapter 14. Births by order and childlessness in the post-socialist countries.- Chapter 15. On the evaluation of ‘Self-perceived Age’ for Europeans and Americans.- Part IV: Theoretical Issues and Applications.- Chapter 16. Spatio-temporal aspects of community well-being in Multivariate Functional Data approach.- Chapter 17. Properties and Dynamics of the Beta Gompertz Generalized Makeham Distribution.- Chapter 18. Increasing efficiency in the EBT algorithm.- Chapter 19. Psychometric validation of constructs defined by ordinal-valued items.- Chapter 20. Robust Minimal Markov Model for Dengue Virus Type 3.- Chapter 21. Determining influential factors in spatio-temporal models.- Chapter 22. Describing labour market dynamics through Non Homogeneous Markov System theory.- Part V: Life-time, Survival, Pension, Labor Force and Further Estimates.- Chapter 23. The wide variety of regression models for lifetime data.- Chapter 24. Analysing the risk of bankruptcy of firms: survival analysis, competing risks and multistate models.- Chapter 25. A bayesian modeling approach to private preparedness behavior against flood hazards.- Chapter 26. Assessing labour market mobility in Europe.- Chapter 27. The implications of applying alternative-supplementary measures of the unemployment rate to regions: Evidence from the European Union Labour Force Survey for Southern Europe, 2008-2015.- Chapter 28. Reverse Mortgages: Risks and Opportunities.- Chapter 29. Estimating the Health State at Retirement: A Stochastic Modeling Approach.
Despre autor
Christos H. Skiadas, Ph D, was the founder and director of the Data Analysis and Forecasting Laboratory at the Technical University of Crete. He is chair of the Demographics Workshop series, the Applied Stochastic Models and Data Analysis Conference series and the Chaotic Modeling and Simulation Conference series. He has published more than 80 papers, three monographs, and 18 books, including probability, statistics, data analysis and forecasting. His research interests include innovation diffusion modeling and forecasting, life table data modeling, healthy life expectancy estimates, and deterministic, stochastic, and chaotic modeling. Charilaos Skiadas, Ph D, is an associate professor in mathematics and computer science at Hanover College. His research interests encompass a wide array of mathematical and computing topics, ranging from algebraic geometry to statistics and programming languages to data science and health state modeling.
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