Age Period Cohort Models

Author: Robert O'Brien
Publisher: CRC Press
ISBN: 1466551534
Format: PDF, Mobi
Download Now
Develop a Deep Understanding of the Statistical Issues of APC Analysis Age–Period–Cohort Models: Approaches and Analyses with Aggregate Data presents an introduction to the problems and strategies for modeling age, period, and cohort (APC) effects for aggregate-level data. These strategies include constrained estimation, the use of age and/or period and/or cohort characteristics, estimable functions, variance decomposition, and a new technique called the s-constraint approach. See How Common Methods Are Related to Each Other After a general and wide-ranging introductory chapter, the book explains the identification problem from algebraic and geometric perspectives and discusses constrained regression. It then covers important strategies that provide information that does not directly depend on the constraints used to identify the APC model. The final chapter presents a specific empirical example showing that a combination of the approaches can make a compelling case for particular APC effects. Get Answers to Questions about the Relationships of Ages, Periods, and Cohorts to Important Substantive Variables This book incorporates several APC approaches into one resource, emphasizing both their geometry and algebra. This integrated presentation helps researchers effectively judge the strengths and weaknesses of the methods, which should lead to better future research and better interpretation of existing research.

Age Period Cohort Analysis

Author: Yang Yang
Publisher: CRC Press
ISBN: 1466507535
Format: PDF, ePub, Mobi
Download Now
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.

A Practical Guide to Age Period Cohort Analysis

Author: Wenjiang Fu
Publisher: CRC Press
ISBN: 1466592664
Format: PDF, Docs
Download Now
Age-Period-Cohort analysis has a wide range of applications, from chronic disease incidence and mortality data in public health and epidemiology, to many social events (birth, death, marriage, etc) in social sciences and demography, and most recently investment, healthcare and pension contribution in economics and finance. Although APC analysis has been studied for the past 40 years and a lot of methods have been developed, the identification problem has been a major hurdle in analyzing APC data, where the regression model has multiple estimators, leading to indetermination of parameters and temporal trends. A Practical Guide to Age-Period Cohort Analysis: The Identification Problem and Beyond provides practitioners a guide to using APC models as well as offers graduate students and researchers an overview of the current methods for APC analysis while clarifying the confusion of the identification problem by explaining why some methods address the problem well while others do not. Features · Gives a comprehensive and in-depth review of models and methods in APC analysis. · Provides an in-depth explanation of the identification problem and statistical approaches to addressing the problem and clarifying the confusion. · Utilizes real data sets to illustrate different data issues that have not been addressed in the literature, including unequal intervals in age and period groups, etc. Contains step-by-step modeling instruction and R programs to demonstrate how to conduct APC analysis and how to conduct prediction for the future Reflects the most recent development in APC modeling and analysis including the intrinsic estimator Wenjiang Fu is a professor of statistics at the University of Houston. Professor Fu’s research interests include modeling big data, applied statistics research in health and human genome studies, and analysis of complex economic and social science data.

Applied Survey Data Analysis

Author: Steven G. Heeringa
Publisher: CRC Press
ISBN: 9781420080674
Format: PDF, ePub, Mobi
Download Now
Taking a practical approach that draws on the authors’ extensive teaching, consulting, and research experiences, Applied Survey Data Analysis provides an intermediate-level statistical overview of the analysis of complex sample survey data. It emphasizes methods and worked examples using available software procedures while reinforcing the principles and theory that underlie those methods. After introducing a step-by-step process for approaching a survey analysis problem, the book presents the fundamental features of complex sample designs and shows how to integrate design characteristics into the statistical methods and software for survey estimation and inference. The authors then focus on the methods and models used in analyzing continuous, categorical, and count-dependent variables; event history; and missing data problems. Some of the techniques discussed include univariate descriptive and simple bivariate analyses, the linear regression model, generalized linear regression modeling methods, the Cox proportional hazards model, discrete time models, and the multiple imputation analysis method. The final chapter covers new developments in survey applications of advanced statistical techniques, including model-based analysis approaches. Designed for readers working in a wide array of disciplines who use survey data in their work, this book also provides a useful framework for integrating more in-depth studies of the theory and methods of survey data analysis. A guide to the applied statistical analysis and interpretation of survey data, it contains many examples and practical exercises based on major real-world survey data sets. Although the authors use Stata for most examples in the text, they offer SAS, SPSS, SUDAAN, R, WesVar, IVEware, and Mplus software code for replicating the examples on the book’s website: http://www.isr.umich.edu/src/smp/asda/

A Life Course Perspective on Health Trajectories and Transitions

Author: Claudine Burton-Jeangros
Publisher: Springer
ISBN: 331920484X
Format: PDF, Docs
Download Now
This open access book examines health trajectories and health transitions at different stages of the life course, including childhood, adulthood and later life. It provides findings that assess the role of biological and social transitions on health status over time. The essays examine a wide range of health issues, including the consequences of military service on body mass index, childhood obesity and cardiovascular health, socio-economic inequalities in preventive health care use, depression and anxiety during the child rearing period, health trajectories and transitions in people with cystic fibrosis and oral health over the life course. The book addresses theoretical, empirical and methodological issues as well as examines different national contexts, which help to identify factors of vulnerability and potential resources that support resilience available for specific groups and/or populations. Health reflects the ability of individuals to adapt to their social environment. This book analyzes health as a dynamic experience. It examines how different aspects of individual health unfold over time as a result of aging but also in relation to changing socioeconomic conditions. It also offers readers potential insights into public policies that affect the health status of a population.

Survival Analysis Using S

Author: Mara Tableman
Publisher: CRC Press
ISBN: 9780203501412
Format: PDF, Docs
Download Now
Survival Analysis Using S: Analysis of Time-to-Event Data is designed as a text for a one-semester or one-quarter course in survival analysis for upper-level or graduate students in statistics, biostatistics, and epidemiology. Prerequisites are a standard pre-calculus first course in probability and statistics, and a course in applied linear regression models. No prior knowledge of S or R is assumed. A wide choice of exercises is included, some intended for more advanced students with a first course in mathematical statistics. The authors emphasize parametric log-linear models, while also detailing nonparametric procedures along with model building and data diagnostics. Medical and public health researchers will find the discussion of cut point analysis with bootstrap validation, competing risks and the cumulative incidence estimator, and the analysis of left-truncated and right-censored data invaluable. The bootstrap procedure checks robustness of cut point analysis and determines cut point(s). In a chapter written by Stephen Portnoy, censored regression quantiles - a new nonparametric regression methodology (2003) - is developed to identify important forms of population heterogeneity and to detect departures from traditional Cox models. By generalizing the Kaplan-Meier estimator to regression models for conditional quantiles, this methods provides a valuable complement to traditional Cox proportional hazards approaches.

A Handbook of Statistical Analyses Using SPSS

Author: Sabine Landau
Publisher: Kogan Page Publishers
ISBN: 9781584883692
Format: PDF, Mobi
Download Now
This text describes how to conduct a range of univariate and multivariate statistical analyses using the latest version of the Statistical Package for the Social Sciences, SPSS 11.

Doing Data Science

Author: Cathy O'Neil
Publisher: "O'Reilly Media, Inc."
ISBN: 144936389X
Format: PDF, Mobi
Download Now
Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science. Topics include: Statistical inference, exploratory data analysis, and the data science process Algorithms Spam filters, Naive Bayes, and data wrangling Logistic regression Financial modeling Recommendation engines and causality Data visualization Social networks and data journalism Data engineering, MapReduce, Pregel, and Hadoop Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course.

Weber and Durkheim

Author: Henrik Jensen
Publisher: Routledge
ISBN: 1136296735
Format: PDF, Kindle
Download Now
Weber and Durkheim: A methodological comparison is a systematic, comparative analysis of the methodologies of Max Weber and Émile Durkheim. Jensen shows how Weber and Durkheim analyse Protestants and Catholics in practice in The Protestant Ethic and Suicide, respectively. The very different ways that Weber and Durkheim carry out their analyses are then used to describe, analyse and contrast their methodological principles and points of view, raising fundamental questions in sociological and social science analysis, such as: What constitutes the object of sociology? How are concepts developed? What status can be attributed to laws? Which possibilities – and limitations – do we have for producing scientific insight into society? What are we to think of the relationship between ‘Is’ and ‘Ought’ – and how can social science deal with values? How are social phenomena to be explained? This book will be a valuable resource for students and scholars of sociology, social methodology, political theory, political science, social theory and philosophy.

Big Data and Social Science

Author: Ian Foster
Publisher: CRC Press
ISBN: 1498751431
Format: PDF, ePub, Docs
Download Now
Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website.