Kenneth C. Land – författare

Age-Period-Cohort Analysis: New Models, Methods, and Empirical Applications is based on a decade of the authors’ collaborative work in age-period-cohort (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. The authors 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.The book makes two essential contributions to quantitative studies of time-related change. Through the introduction of the GLMM framework, it shows how innovative estimation methods and new model specifications can be used to tackle the "model identification problem" that has hampered the development and empirical application of APC analysis. The book also addresses the major criticism against APC analysis by explaining the use of new models within the GLMM framework to uncover mechanisms underlying age patterns and temporal trends. Encompassing both methodological expositions and empirical studies, this book explores the ways in which statistical models, methods, and research designs can be used to open new possibilities for APC analysis. It compares new and existing models and methods and provides useful guidelines on how to conduct APC analysis. For empirical illustrations, the text incorporates examples from a variety of disciplines, such as sociology, demography, and epidemiology. Along with details on empirical analyses, software and programs to estimate the models are available on the book’s web page.

Supported by real-world case studies, this essential textbook provides a detailed overview of the use of biostatistical tools and methods, enabling students and researchers to undertake their own research with confidence and understanding.After a general introduction to the field, the book provides a step-by-step description of the essential statistical methods that are foundational to analysing data from clinical trials, epidemiological studies and other health-related research. From basic concepts such as probability and distribution through to hypothesis testing, regression analysis, survival analysis, meta-analysis and systematic reviews, each chapter is designed with a clear pedagogical approach featuring explanatory diagrams, real-life examples and sample problems. Later sections of the book cover clinical trial design and analysis, diagnostic testing, Bayesian methods and machine learning. Through this detailed, comprehensive treatment of the key tools and methods, the book encourages readers to develop their own critical thinking skills, recognising good or bad pieces of research when they see them, asking questions about where evidence and assumptions come from or choosing the most appropriate biostatistical methodologies in their own research.Written by a team of experts with extensive teaching experience in this field, this is the ideal textbook for graduate students and researchers across the biomedical sciences, from public health to epidemiology to clinical medicine.

Supported by real-world case studies, this essential textbook provides a detailed overview of the use of biostatistical tools and methods, enabling students and researchers to undertake their own research with confidence and understanding.After a general introduction to the field, the book provides a step-by-step description of the essential statistical methods that are foundational to analysing data from clinical trials, epidemiological studies and other health-related research. From basic concepts such as probability and distribution through to hypothesis testing, regression analysis, survival analysis, meta-analysis and systematic reviews, each chapter is designed with a clear pedagogical approach featuring explanatory diagrams, real-life examples and sample problems. Later sections of the book cover clinical trial design and analysis, diagnostic testing, Bayesian methods and machine learning. Through this detailed, comprehensive treatment of the key tools and methods, the book encourages readers to develop their own critical thinking skills, recognising good or bad pieces of research when they see them, asking questions about where evidence and assumptions come from or choosing the most appropriate biostatistical methodologies in their own research.Written by a team of experts with extensive teaching experience in this field, this is the ideal textbook for graduate students and researchers across the biomedical sciences, from public health to epidemiology to clinical medicine.

Age-Period-Cohort Analysis: New Models, Methods, and Empirical Applications is based on a decade of the authors’ collaborative work in age-period-cohort (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. The authors 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.The book makes two essential contributions to quantitative studies of time-related change. Through the introduction of the GLMM framework, it shows how innovative estimation methods and new model specifications can be used to tackle the "model identification problem" that has hampered the development and empirical application of APC analysis. The book also addresses the major criticism against APC analysis by explaining the use of new models within the GLMM framework to uncover mechanisms underlying age patterns and temporal trends. Encompassing both methodological expositions and empirical studies, this book explores the ways in which statistical models, methods, and research designs can be used to open new possibilities for APC analysis. It compares new and existing models and methods and provides useful guidelines on how to conduct APC analysis. For empirical illustrations, the text incorporates examples from a variety of disciplines, such as sociology, demography, and epidemiology. Along with details on empirical analyses, software and programs to estimate the models are available on the book’s web page.

This book presents an innovative demographic toolkit known as the ProFamy extended cohort-component method for the projection of household structures and living arrangements with empirical applications to the United States, the largest developed country, and China, the largest developing country.

The aim of the Handbook of Social Indicators and Quality of Life Research is to create an overview of the field of Quality of Life (QOL) studies in the early years of the 21st century that can be updated and improved upon as the field evolves and the century unfolds. Social indicators are statistical time series “…used to monitor the social system, helping to identify changes and to guide intervention to alter the course of social change”. Examples include unemployment rates, crime rates, estimates of life expectancy, health status indices, school enrollment rates, average achievement scores, election voting rates, and measures of subjective well-being such as satisfaction with life-as-a-whole and with specific domains or aspects of life. This book provides a review of the historical development of the field including the history of QOL in medicine and mental health as well as the research related to quality-of-work-life (QWL) programs. It discusses several of QOL main concepts: happiness, positive psychology, and subjective wellbeing. Relations between spirituality and religiousness and QOL are examined as are the effects of educational attainment on QOL and marketing, and the associations with economic growth. The book goes on to investigate methodological approaches and issues that should be considered in measuring and analysing quality of life from a quantitative perspective. The final chapters are dedicated to research on elements of QOL in a broad range of countries and populations.

In 1998, the Foundation for Child Development (FCD) provided Kenneth Land a grant to explore the feasibility of producing the first national composite index of the status of American children that would chart changes in their well-being over time. Important questions needed to be answered: was it possible to trace trends in child and youth well-being over several decades?  Could such an index provide a way of determining whether the United States was making progress in improving its children’s lives? The Index of Child and Youth Well-Being (CWI) was born from these questions.   Viewing the CWI trends from 1975 to present, there is evidence that the well-being of American children lags behind other Western nations. As conditions change, it is clear that the index is an evolving and rich enterprise. This volume attests to that evolution, and what the CWI promises for understanding the progress – or lack of progress – in enhancing the life prospects of all American children.  ​

This project had its origins in discussions of social forecasts and forecasting method­ ologies initiated a few years ago by several social and natural science members of the Social Science Research Council's Committee on Social Indicators.

This volume is a critical exposition of the data and analyses from a full decade of rigorous research into how age-related changes at the individual level, along with other factors, contribute to morbidity, disability and mortality risks at the broader population level. After summarizing the state of our knowledge in the field, individual chapters offer enlightening discussion on a range of key topics such as age trajectory analysis in select and general populations, incidence/age patterns of major chronic illnesses, and indices of cumulative deficits and their use in characterizing and understanding the detailed properties of individual aging.The book features comprehensive statistical analyses of unique longitudinal data sets including the unique resource of the Framingham Heart Study, with its more than 60 years of follow-up. Culminating in penetrating conclusions about the insights gained from the work involved, this book adds much to our understanding of the links between aging and human health.

The aim of the Handbook of Social Indicators and Quality of Life Research is to create an overview of the field of Quality of Life (QOL) studies in the early years of the 21st century that can be updated and improved upon as the field evolves and the century unfolds. Social indicators are statistical time series “…used to monitor the social system, helping to identify changes and to guide intervention to alter the course of social change”. Examples include unemployment rates, crime rates, estimates of life expectancy, health status indices, school enrollment rates, average achievement scores, election voting rates, and measures of subjective well-being such as satisfaction with life-as-a-whole and with specific domains or aspects of life. This book provides a review of the historical development of the field including the history of QOL in medicine and mental health as well as the research related to quality-of-work-life (QWL) programs. It discusses several of QOL main concepts: happiness, positive psychology, and subjective wellbeing. Relations between spirituality and religiousness and QOL are examined as are the effects of educational attainment on QOL and marketing, and the associations with economic growth. The book goes on to investigate methodological approaches and issues that should be considered in measuring and analysing quality of life from a quantitative perspective. The final chapters are dedicated to research on elements of QOL in a broad range of countries and populations.

In 1998, the Foundation for Child Development (FCD) provided Kenneth Land a grant to explore the feasibility of producing the first national composite index of the status of American children that would chart changes in their well-being over time. Important questions needed to be answered: was it possible to trace trends in child and youth well-being over several decades?  Could such an index provide a way of determining whether the United States was making progress in improving its children’s lives? The Index of Child and Youth Well-Being (CWI) was born from these questions.   Viewing the CWI trends from 1975 to present, there is evidence that the well-being of American children lags behind other Western nations. As conditions change, it is clear that the index is an evolving and rich enterprise. This volume attests to that evolution, and what the CWI promises for understanding the progress – or lack of progress – in enhancing the life prospects of all American children.  ​

This book presents an innovative demographic toolkit known as the ProFamy extended cohort-component method for the projection of household structures and living arrangements with empirical applications to the United States, the largest developed country, and China, the largest developing country. The ProFamy method uses demographic rates as inputs to project detailed distributions of household types and sizes, living arrangements of all household members, and population by age, sex, race/ethnicity, and urban/rural residence at national, sub-national, or small area levels.  It can also project elderly care needs and costs, pension deficits, and household consumption. The ProFamy method presented herein has substantial merits compared to the traditional headship rate method, which is not linked to demographic rates and projects limited household types without other household members than "heads".The book consists of four parts. The first part presents the methodology, data, estimation issues, and empirical assessments. The next parts present applications in the United States (part two) and China (part three), concerning demographic, social, economic, and business research; policy analysis, including forecasting future trends of household type/size, elderly living arrangements, disability, and home-based care costs, and household consumption including housing and vehicles. The fourth part includes a user’s guide for the ProFamy software to project households, living arrangements, and home-based consumptions.This book offers an invaluable toolkit for researchers, analysts and students in academic, public and private businesses, whose work is related to levels and rates of change in households, population and consumption patterns.