Applied Longitudinal Analysis

Author: Garrett M. Fitzmaurice,Nan M. Laird,James H. Ware

Publisher: John Wiley & Sons

ISBN: 1118551796

Category: Mathematics

Page: 740

View: 6417

Praise for the First Edition ". . . [this book] should be on the shelf of everyone interestedin . . . longitudinal data analysis." —Journal of the American Statistical Association Features newly developed topics and applications of theanalysis of longitudinal data Applied Longitudinal Analysis, Second Edition presentsmodern methods for analyzing data from longitudinal studies and nowfeatures the latest state-of-the-art techniques. The bookemphasizes practical, rather than theoretical, aspects of methodsfor the analysis of diverse types of longitudinal data that can beapplied across various fields of study, from the health and medicalsciences to the social and behavioral sciences. The authors incorporate their extensive academic and researchexperience along with various updates that have been made inresponse to reader feedback. The Second Edition features six newlyadded chapters that explore topics currently evolving in the field,including: Fixed effects and mixed effects models Marginal models and generalized estimating equations Approximate methods for generalized linear mixed effectsmodels Multiple imputation and inverse probability weightedmethods Smoothing methods for longitudinal data Sample size and power Each chapter presents methods in the setting of applications todata sets drawn from the health sciences. New problem sets havebeen added to many chapters, and a related website features sampleprograms and computer output using SAS, Stata, and R, as well asdata sets and supplemental slides to facilitate a completeunderstanding of the material. With its strong emphasis on multidisciplinary applications andthe interpretation of results, Applied LongitudinalAnalysis, Second Edition is an excellent book for courses onstatistics in the health and medical sciences at theupper-undergraduate and graduate levels. The book also serves as avaluable reference for researchers and professionals in themedical, public health, and pharmaceutical fields as well as thosein social and behavioral sciences who would like to learn moreabout analyzing longitudinal data.

Applied Longitudinal Data Analysis for Epidemiology

A Practical Guide

Author: Jos W. R. Twisk

Publisher: Cambridge University Press

ISBN: 9780521525800

Category: Medical

Page: 301

View: 2850

The most important techniques available for longitudinal data analysis are discussed in this book. The discussion includes simple techniques such as the paired t-test and summary statistics, but also more sophisticated techniques such as generalized estimating equations and random coefficient analysis. A distinction is made between longitudinal analysis with continuous, dichotomous, and categorical outcome variables. This practical guide is especially suitable for non-statisticians and all those undertaking medical research or epidemiological studies.

Applied Longitudinal Data Analysis

Modeling Change and Event Occurrence

Author: Judith D. Singer,John B. Willett

Publisher: Oxford University Press

ISBN: 0199882401

Category: Psychology

Page: 644

View: 6442

Change is constant in everyday life. Infants crawl and then walk, children learn to read and write, teenagers mature in myriad ways, the elderly become frail and forgetful. Beyond these natural processes and events, external forces and interventions instigate and disrupt change: test scores may rise after a coaching course, drug abusers may remain abstinent after residential treatment. By charting changes over time and investigating whether and when events occur, researchers reveal the temporal rhythms of our lives. Applied Longitudinal Data Analysis is a much-needed professional book for empirical researchers and graduate students in the behavioral, social, and biomedical sciences. It offers the first accessible in-depth presentation of two of today's most popular statistical methods: multilevel models for individual change and hazard/survival models for event occurrence (in both discrete- and continuous-time). Using clear, concise prose and real data sets from published studies, the authors take you step by step through complete analyses, from simple exploratory displays that reveal underlying patterns through sophisticated specifications of complex statistical models. Applied Longitudinal Data Analysis offers readers a private consultation session with internationally recognized experts and represents a unique contribution to the literature on quantitative empirical methods. Visit http://www.ats.ucla.edu/stat/examples/alda.htm for: · Downloadable data sets · Library of computer programs in SAS, SPSS, Stata, HLM, MLwiN, and more · Additional material for data analysis

Longitudinal Data Analysis

Author: Garrett Fitzmaurice,Marie Davidian,Geert Verbeke,Geert Molenberghs

Publisher: CRC Press

ISBN: 9781420011579

Category: Mathematics

Page: 632

View: 7135

Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory and applications. It also focuses on the assorted challenges that arise in analyzing longitudinal data. After discussing historical aspects, leading researchers explore four broad themes: parametric modeling, nonparametric and semiparametric methods, joint models, and incomplete data. Each of these sections begins with an introductory chapter that provides useful background material and a broad outline to set the stage for subsequent chapters. Rather than focus on a narrowly defined topic, chapters integrate important research discussions from the statistical literature. They seamlessly blend theory with applications and include examples and case studies from various disciplines. Destined to become a landmark publication in the field, this carefully edited collection emphasizes statistical models and methods likely to endure in the future. Whether involved in the development of statistical methodology or the analysis of longitudinal data, readers will gain new perspectives on the field.

Longitudinal Analysis

Modeling Within-Person Fluctuation and Change

Author: Lesa Hoffman

Publisher: Routledge

ISBN: 1317591089

Category: Psychology

Page: 654

View: 7591

Longitudinal Analysis provides an accessible, application-oriented treatment of introductory and advanced linear models for within-person fluctuation and change. Organized by research design and data type, the text uses in-depth examples to provide a complete description of the model-building process. The core longitudinal models and their extensions are presented within a multilevel modeling framework, paying careful attention to the modeling concerns that are unique to longitudinal data. Written in a conversational style, the text provides verbal and visual interpretation of model equations to aid in their translation to empirical research results. Overviews and summaries, boldfaced key terms, and review questions will help readers synthesize the key concepts in each chapter. Written for non-mathematically-oriented readers, this text features: A description of the data manipulation steps required prior to model estimation so readers can more easily apply the steps to their own data An emphasis on how the terminology, interpretation, and estimation of familiar general linear models relates to those of more complex models for longitudinal data Integrated model comparisons, effect sizes, and statistical inference in each example to strengthen readers’ understanding of the overall model-building process Sample results sections for each example to provide useful templates for published reports Examples using both real and simulated data in the text, along with syntax and output for SPSS, SAS, STATA, and Mplus at www.PilesOfVariance.com to help readers apply the models to their own data The book opens with the building blocks of longitudinal analysis—general ideas, the general linear model for between-person analysis, and between- and within-person models for the variance and the options within repeated measures analysis of variance. Section 2 introduces unconditional longitudinal models including alternative covariance structure models to describe within-person fluctuation over time and random effects models for within-person change. Conditional longitudinal models are presented in section 3, including both time-invariant and time-varying predictors. Section 4 reviews advanced applications, including alternative metrics of time in accelerated longitudinal designs, three-level models for multiple dimensions of within-person time, the analysis of individuals in groups over time, and repeated measures designs not involving time. The book concludes with additional considerations and future directions, including an overview of sample size planning and other model extensions for non-normal outcomes and intensive longitudinal data. Class-tested at the University of Nebraska-Lincoln and in intensive summer workshops, this is an ideal text for graduate-level courses on longitudinal analysis or general multilevel modeling taught in psychology, human development and family studies, education, business, and other behavioral, social, and health sciences. The book’s accessible approach will also help those trying to learn on their own. Only familiarity with general linear models (regression, analysis of variance) is needed for this text.

Medizinische Statistik

Author: Hans J. Trampisch,Jürgen Windeler

Publisher: Springer-Verlag

ISBN: 364256996X

Category: Mathematics

Page: 376

View: 7345

"Statistiken sind merkwürdige Dinge ...", dies wird so mancher Mediziner denken, wenn er sich mit der Biometrie befaßt. Sei es im Rahmen seiner Ausbildung oder im Zuge wissenschaftlicher oder klinischer Studien, Kenntnisse der Statistik und Mathematik sind unentbehrlich für die tägliche Arbeit des Mediziners. Ziel dieses Lehrbuches ist es, den Mediziner systematisch an biometrische Terminologie und Arbeitsmethoden heranzuführen, um ihn schließlich mit den Grundlagen der Wahrscheinlichkeitsrechung vertraut zu machen. Nach der Lektüre dieses Buches hält der Leser ein Werkzeug in den Händen, das ihm bei der Lösung medizinscher Fragestellungen hilft ebenso wie bei der Beschreibung von Ergebnissen wissenschaftlicher Studien und natürlich bei der Doktorarbeit!

Handbook of Missing Data Methodology

Author: Geert Molenberghs,Garrett Fitzmaurice,Michael G. Kenward,Anastasios Tsiatis,Geert Verbeke

Publisher: CRC Press

ISBN: 1439854629

Category: Mathematics

Page: 600

View: 2108

Missing data affect nearly every discipline by complicating the statistical analysis of collected data. But since the 1990s, there have been important developments in the statistical methodology for handling missing data. Written by renowned statisticians in this area, Handbook of Missing Data Methodology presents many methodological advances and the latest applications of missing data methods in empirical research. Divided into six parts, the handbook begins by establishing notation and terminology. It reviews the general taxonomy of missing data mechanisms and their implications for analysis and offers a historical perspective on early methods for handling missing data. The following three parts cover various inference paradigms when data are missing, including likelihood and Bayesian methods; semi-parametric methods, with particular emphasis on inverse probability weighting; and multiple imputation methods. The next part of the book focuses on a range of approaches that assess the sensitivity of inferences to alternative, routinely non-verifiable assumptions about the missing data process. The final part discusses special topics, such as missing data in clinical trials and sample surveys as well as approaches to model diagnostics in the missing data setting. In each part, an introduction provides useful background material and an overview to set the stage for subsequent chapters. Covering both established and emerging methodologies for missing data, this book sets the scene for future research. It provides the framework for readers to delve into research and practical applications of missing data methods.

Biostatistics for Animal Science

Author: Miroslav Kaps,William R. Lamberson

Publisher: CABI

ISBN: 1845935403

Category: Technology & Engineering

Page: 504

View: 7222

Designed to cover techniques for analysis of data in the animal sciences, this textbook provides an overview of the basic principles of statistics enabling the subsequent applications to be carried out with familiarity and understanding, followed by more complex applications and detailed procedures commonly used in animal sciences. Each chapter begins by introducing a problem with practical questions, followed by a brief theoretical background, and is supplemented with an abundance of examples in SAS from animal sciences and related fields. Key features: - New larger format and updated throughout - Covers both basic techniques and more complex procedures - Contains exercises for readers to work through

Handbook of Cognitive Aging

Interdisciplinary Perspectives

Author: Scott M. Hofer,Duane F Alwin

Publisher: SAGE

ISBN: 145227892X

Category: Psychology

Page: 744

View: 4748

"Provides a unique perspective. I am particularly impressed with the sections on innovative design and methods to investigate cognitive aging and the integrative perspectives. None of the existing texts covers this material to the same level." —Donna J. La Voie, Saint Louis University "The emphasis on integrating the literature with theoretical and methodological innovations could have a far-reaching impact on the field." —Deb McGinnis, Oakland University The Handbook of Cognitive Aging: Interdisciplinary Perspectives clarifies the differences in patterns and processes of cognitive aging. Along with a comprehensive review of current research, editors Scott M. Hofer and Duane F. Alwin provide a solid foundation for building a multidisciplinary agenda that will stimulate further rigorous research into these complex factors. Key Features Gathers the widest possible range of perspectives by including cognitive aging experts in various disciplines while maintaining a degree of unity across chapters Examines the limitations of the extant literature, particularly in research design and measurement, and offers new suggestions to guide future research Highlights the broad scope of the field with topics ranging from demography to development to neuroscience, offering the most complete coverage available on cognitive aging

Wellbeing: A Complete Reference Guide, Work and Wellbeing

Author: Peter Y. Chen,Cary L. Cooper

Publisher: John Wiley & Sons

ISBN: 1118716213

Category: Psychology

Page: 536

View: 5817

Part of the six-volume reference set Wellbeing: A Complete Reference Guide, this volume is a comprehensive look at wellbeing in the workplace at organizational, managerial, and individual levels. Discusses the implications of theory and practice in the field of workplace wellbeing Incorporates not only coverage of workplace stress in relation to wellbeing, but also aspects of positive psychology Explores the role of governments in promoting work place well being Part of the six-volume set Wellbeing: A Complete Reference Guide, which brings together leading research on wellbeing from across the social sciences Topics include work-life balance; coping strategies and characters of individuals; characteristics of workplaces and organizational strategies that are conducive to wellbeing; and many more

Linear Models

The Theory and Application of Analysis of Variance

Author: Brenton R. Clarke

Publisher: John Wiley & Sons

ISBN: 9780470377970

Category: Mathematics

Page: 288

View: 8889

An insightful approach to the analysis of variance in the study of linear models Linear Models explores the theory of linear models and the dynamic relationships that these models have with Analysis of Variance (ANOVA), experimental design, and random and mixed-model effects. This one-of-a-kind book emphasizes an approach that clearly explains the distribution theory of linear models and experimental design starting from basic mathematical concepts in linear algebra. The author begins with a presentation of the classic fixed-effects linear model and goes on to illustrate eight common linear models, along with the value of their use in statistics. From this foundation, subsequent chapters introduce concepts pertaining to the linear model, starting with vector space theory and the theory of least-squares estimation. An outline of the Helmert matrix is also presented, along with a thorough explanation of how the ANOVA is created in both typical two-way and higher layout designs, ultimately revealing the distribution theory. Other important topics covered include: Vector space theory The theory of least squares estimation Gauss-Markov theorem Kronecker products Diagnostic and robust methods for linear models Likelihood approaches to estimation A discussion of Bayesian theory is also included for purposes of comparison and contrast, and numerous illustrative exercises assist the reader with uncovering the nature of the models, using both classic and new data sets. Requiring only a working knowledge of basic probability and statistical inference, Linear Models is a valuable book for courses on linear models at the upper-undergraduate and graduate levels. It is also an excellent reference for practitioners who use linear models to conduct research in the fields of econometrics, psychology, sociology, biology, and agriculture.

Loss Models

From Data to Decisions

Author: Stuart A. Klugman,Harry H. Panjer,Gordon E. Willmot

Publisher: John Wiley & Sons

ISBN: 0470391332

Category: Business & Economics

Page: 784

View: 2292

The EM Algorithm and Extensions

Author: Geoffrey McLachlan,Thriyambakam Krishnan

Publisher: John Wiley & Sons

ISBN: 0470191600

Category: Mathematics

Page: 384

View: 9274

The only single-source——now completely updated and revised——to offer a unified treatment of the theory, methodology, and applications of the EM algorithm Complete with updates that capture developments from the past decade, The EM Algorithm and Extensions, Second Edition successfully provides a basic understanding of the EM algorithm by describing its inception, implementation, and applicability in numerous statistical contexts. In conjunction with the fundamentals of the topic, the authors discuss convergence issues and computation of standard errors, and, in addition, unveil many parallels and connections between the EM algorithm and Markov chain Monte Carlo algorithms. Thorough discussions on the complexities and drawbacks that arise from the basic EM algorithm, such as slow convergence and lack of an in-built procedure to compute the covariance matrix of parameter estimates, are also presented. While the general philosophy of the First Edition has been maintained, this timely new edition has been updated, revised, and expanded to include: New chapters on Monte Carlo versions of the EM algorithm and generalizations of the EM algorithm New results on convergence, including convergence of the EM algorithm in constrained parameter spaces Expanded discussion of standard error computation methods, such as methods for categorical data and methods based on numerical differentiation Coverage of the interval EM, which locates all stationary points in a designated region of the parameter space Exploration of the EM algorithm's relationship with the Gibbs sampler and other Markov chain Monte Carlo methods Plentiful pedagogical elements—chapter introductions, lists of examples, author and subject indices, computer-drawn graphics, and a related Web site The EM Algorithm and Extensions, Second Edition serves as an excellent text for graduate-level statistics students and is also a comprehensive resource for theoreticians, practitioners, and researchers in the social and physical sciences who would like to extend their knowledge of the EM algorithm.

Periodically Correlated Random Sequences

Spectral Theory and Practice

Author: Harry L. Hurd,Abolghassem Miamee

Publisher: John Wiley & Sons

ISBN: 9780470182826

Category: Mathematics

Page: 384

View: 3102

Uniquely combining theory, application, and computing, this book explores the spectral approach to time series analysis The use of periodically correlated (or cyclostationary) processes has become increasingly popular in a range of research areas such as meteorology, climate, communications, economics, and machine diagnostics. Periodically Correlated Random Sequences presents the main ideas of these processes through the use of basic definitions along with motivating, insightful, and illustrative examples. Extensive coverage of key concepts is provided, including second-order theory, Hilbert spaces, Fourier theory, and the spectral theory of harmonizable sequences. The authors also provide a paradigm for nonparametric time series analysis including tests for the presence of PC structures. Features of the book include: An emphasis on the link between the spectral theory of unitary operators and the correlation structure of PC sequences A discussion of the issues relating to nonparametric time series analysis for PC sequences, including estimation of the mean, correlation, and spectrum A balanced blend of historical background with modern application-specific references to periodically correlated processes An accompanying Web site that features additional exercises as well as data sets and programs written in MATLAB® for performing time series analysis on data that may have a PC structure Periodically Correlated Random Sequences is an ideal text on time series analysis for graduate-level statistics and engineering students who have previous experience in second-order stochastic processes (Hilbert space), vector spaces, random processes, and probability. This book also serves as a valuable reference for research statisticians and practitioners in areas of probability and statistics such as time series analysis, stochastic processes, and prediction theory.

Healthy Eating and Physical Activity in Out-of-School Time Settings

New Directions for Youth Development, Number 143

Author: Jean L. Wiecha,Georgia Hall

Publisher: John Wiley & Sons

ISBN: 1119045754

Category: Education

Page: 128

View: 6217

The evidence base of the impact and effectiveness of healthy eating and physical activity interventions in the out-of-school setting is continuing to emerge. By sponsoring this special issue, the National AfterSchool Association provides a platform for the sharing of a range of research studies that can inform and shape current discussion of best policies and practices to support child and youth wellness. The body of work presented in this issue adds considerably to our knowledge of healthy eating and physical activity interventions in out-of-school programs, and highlights the substantial contribution towards childhood obesity prevention that we envision from our field. This is the 143rd volume of New Directions for Youth Development, the Jossey-Bass quarterly report series dedicated to bringing together everyone concerned with helping young people, including scholars, practitioners, and people from different disciplines and professions.

Modes of Parametric Statistical Inference

Author: Seymour Geisser,Wesley O. Johnson

Publisher: John Wiley & Sons

ISBN: 0471743127

Category: Mathematics

Page: 192

View: 5826

A fascinating investigation into the foundations of statisticalinference This publication examines the distinct philosophical foundations ofdifferent statistical modes of parametric inference. Unlike manyother texts that focus on methodology and applications, this bookfocuses on a rather unique combination of theoretical andfoundational aspects that underlie the field of statisticalinference. Readers gain a deeper understanding of the evolution andunderlying logic of each mode as well as each mode's strengths andweaknesses. The book begins with fascinating highlights from the history ofstatistical inference. Readers are given historical examples ofstatistical reasoning used to address practical problems that arosethroughout the centuries. Next, the book goes on to scrutinize fourmajor modes of statistical inference: * Frequentist * Likelihood * Fiducial * Bayesian The author provides readers with specific examples andcounterexamples of situations and datasets where the modes yieldboth similar and dissimilar results, including a violation of thelikelihood principle in which Bayesian and likelihood methodsdiffer from frequentist methods. Each example is followed by adetailed discussion of why the results may have varied from onemode to another, helping the reader to gain a greater understandingof each mode and how it works. Moreover, the author providesconsiderable mathematical detail on certain points to highlight keyaspects of theoretical development. The author's writing style and use of examples make the text clearand engaging. This book is fundamental reading for graduate-levelstudents in statistics as well as anyone with an interest in thefoundations of statistics and the principles underlying statisticalinference, including students in mathematics and the philosophy ofscience. Readers with a background in theoretical statistics willfind the text both accessible and absorbing.