Demography

This book is the first one in which basic demographic models are rigorously formulated by using modern age-structured population dynamics, extended to study real-world population problems.

This book demonstrates different statistical techniques for analyzing health-related data as well as providing new techniques for forecasting and/or projecting the incidence of diseases/disorders.

This authoritative and comprehensive edited volume presents current research on how demography can contribute to generating scientific knowledge and evidence concerning refugees and forced migration, developing evidence based policy recommendations on protection for forced migrants and reception of refugees, and revealing the determinants and consequences of migration for origin and destination regions and communities.

This book provides new theories, applications and quantitative methods in demography, population studies and statistics. It presents and applies data analysis, statistics and stochastic modeling techniques focusing on demography, population aging, mortality and health sciences. The book describes diverse stochastic processes as well as Markov and semi-Markov models in demography and population studies, along with chapters on statistical models and methods in biostatistics and epidemiology. As such the book will be a valuable source to demographers, health scientists, statisticians, economists and sociologists.

This book demonstrates different statistical techniques for analyzing health-related data as well as providing new techniques for forecasting and/or projecting the incidence of diseases/disorders.

This book shows how to use sensitivity analysis in demography. It presents new methods for individuals, cohorts, and populations, with applications to humans, other animals, and plants. The analyses are based on matrix formulations of age-classified, stage-classified, and multistate population models. Methods are presented for linear and nonlinear, deterministic and stochastic, and time-invariant and time-varying cases.