Bayesian Growth Mixture Model For Clustering Longitudinal Data

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Nonparametric Regression Methods for Longitudinal Data Analysis

Author : Hulin Wu
Publisher : John Wiley & Sons
ISBN 13 : 0470009667
Total Pages : 401 pages
Book Rating : 4.4/5 (7 download)

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Book Synopsis Nonparametric Regression Methods for Longitudinal Data Analysis by : Hulin Wu

Download or read book Nonparametric Regression Methods for Longitudinal Data Analysis written by Hulin Wu and published by John Wiley & Sons. This book was released on 2006-05-12 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: Incorporates mixed-effects modeling techniques for more powerful and efficient methods This book presents current and effective nonparametric regression techniques for longitudinal data analysis and systematically investigates the incorporation of mixed-effects modeling techniques into various nonparametric regression models. The authors emphasize modeling ideas and inference methodologies, although some theoretical results for the justification of the proposed methods are presented. With its logical structure and organization, beginning with basic principles, the text develops the foundation needed to master advanced principles and applications. Following a brief overview, data examples from biomedical research studies are presented and point to the need for nonparametric regression analysis approaches. Next, the authors review mixed-effects models and nonparametric regression models, which are the two key building blocks of the proposed modeling techniques. The core section of the book consists of four chapters dedicated to the major nonparametric regression methods: local polynomial, regression spline, smoothing spline, and penalized spline. The next two chapters extend these modeling techniques to semiparametric and time varying coefficient models for longitudinal data analysis. The final chapter examines discrete longitudinal data modeling and analysis. Each chapter concludes with a summary that highlights key points and also provides bibliographic notes that point to additional sources for further study. Examples of data analysis from biomedical research are used to illustrate the methodologies contained throughout the book. Technical proofs are presented in separate appendices. With its focus on solving problems, this is an excellent textbook for upper-level undergraduate and graduate courses in longitudinal data analysis. It is also recommended as a reference for biostatisticians and other theoretical and applied research statisticians with an interest in longitudinal data analysis. Not only do readers gain an understanding of the principles of various nonparametric regression methods, but they also gain a practical understanding of how to use the methods to tackle real-world problems.

Bayesian Smoothing and Regression for Longitudinal, Spatial and Event History Data

Author : Ludwig Fahrmeir
Publisher : OUP Oxford
ISBN 13 : 9780199533022
Total Pages : 0 pages
Book Rating : 4.5/5 (33 download)

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Book Synopsis Bayesian Smoothing and Regression for Longitudinal, Spatial and Event History Data by : Ludwig Fahrmeir

Download or read book Bayesian Smoothing and Regression for Longitudinal, Spatial and Event History Data written by Ludwig Fahrmeir and published by OUP Oxford. This book was released on 2011-04-28 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bringing together recent advances in smoothing and semiparametric regression from a Bayesian perspective, this book demonstrates, with worked examples, the application of these statistical methods to a variety of fields including forestry, development economics, medicine and marketing.

New Approaches in Classification and Data Analysis

Author : Edwin Diday
Publisher : Springer Science & Business Media
ISBN 13 : 3642511759
Total Pages : 695 pages
Book Rating : 4.6/5 (425 download)

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Book Synopsis New Approaches in Classification and Data Analysis by : Edwin Diday

Download or read book New Approaches in Classification and Data Analysis written by Edwin Diday and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 695 pages. Available in PDF, EPUB and Kindle. Book excerpt: The subject of this book is the analysis and processing of structural or quantitative data with emphasis on classification methods, new algorithms as well as applications in various fields related to data analysis and classification. The book presents the state of the art in world-wide research and application of methods from the fields indicated above and consists of survey papers as well as research papers.

Advances in Latent Variable Mixture Models

Author : Gregory R. Hancock
Publisher : IAP
ISBN 13 : 1607526344
Total Pages : 382 pages
Book Rating : 4.6/5 (75 download)

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Book Synopsis Advances in Latent Variable Mixture Models by : Gregory R. Hancock

Download or read book Advances in Latent Variable Mixture Models written by Gregory R. Hancock and published by IAP. This book was released on 2007-11-01 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: The current volume, Advances in Latent Variable Mixture Models, contains chapters by all of the speakers who participated in the 2006 CILVR conference, providing not just a snapshot of the event, but more importantly chronicling the state of the art in latent variable mixture model research. The volume starts with an overview chapter by the CILVR conference keynote speaker, Bengt Muthén, offering a “lay of the land” for latent variable mixture models before the volume moves to more specific constellations of topics. Part I, Multilevel and Longitudinal Systems, deals with mixtures for data that are hierarchical in nature either due to the data’s sampling structure or to the repetition of measures (of varied types) over time. Part II, Models for Assessment and Diagnosis, addresses scenarios for making judgments about individuals’ state of knowledge or development, and about the instruments used for making such judgments. Finally, Part III, Challenges in Model Evaluation, focuses on some of the methodological issues associated with the selection of models most accurately representing the processes and populations under investigation. It should be stated that this volume is not intended to be a first exposure to latent variable methods. Readers lacking such foundational knowledge are encouraged to consult primary and/or secondary didactic resources in order to get the most from the chapters in this volume. Once armed with the basic understanding of latent variable methods, we believe readers will find this volume incredibly exciting.

Mixed Effects Models for Complex Data

Author : Lang Wu
Publisher : CRC Press
ISBN 13 : 9781420074086
Total Pages : 431 pages
Book Rating : 4.0/5 (74 download)

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Book Synopsis Mixed Effects Models for Complex Data by : Lang Wu

Download or read book Mixed Effects Models for Complex Data written by Lang Wu and published by CRC Press. This book was released on 2009-11-11 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.

Bayesian Data Analysis, Third Edition

Author : Andrew Gelman
Publisher : CRC Press
ISBN 13 : 1439840954
Total Pages : 677 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Bayesian Data Analysis, Third Edition by : Andrew Gelman

Download or read book Bayesian Data Analysis, Third Edition written by Andrew Gelman and published by CRC Press. This book was released on 2013-11-01 with total page 677 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.

New Methods for the Analysis of Change

Author : Linda M. Collins
Publisher : Amer Psychological Assn
ISBN 13 : 9781557987549
Total Pages : 442 pages
Book Rating : 4.9/5 (875 download)

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Book Synopsis New Methods for the Analysis of Change by : Linda M. Collins

Download or read book New Methods for the Analysis of Change written by Linda M. Collins and published by Amer Psychological Assn. This book was released on 2001-01-01 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation Psychologists update the Association's 1991 with 12 studies, many from a conference held at Pennsylvania State University in 1998, and some with comments attached. The topics include differential structural equation modeling of intra-individual variability, combining auto-regressive and latent curve models, and planned missing-data designs for analyzing change. Annotation c. Book News, Inc., Portland, OR (booknews.com).

Mixed Models

Author : Eugene Demidenko
Publisher : John Wiley & Sons
ISBN 13 : 1118091574
Total Pages : 768 pages
Book Rating : 4.1/5 (18 download)

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Book Synopsis Mixed Models by : Eugene Demidenko

Download or read book Mixed Models written by Eugene Demidenko and published by John Wiley & Sons. This book was released on 2013-08-05 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition “This book will serve to greatly complement the growing number of texts dealing with mixed models, and I highly recommend including it in one’s personal library.” —Journal of the American Statistical Association Mixed modeling is a crucial area of statistics, enabling the analysis of clustered and longitudinal data. Mixed Models: Theory and Applications with R, Second Edition fills a gap in existing literature between mathematical and applied statistical books by presenting a powerful examination of mixed model theory and application with special attention given to the implementation in R. The new edition provides in-depth mathematical coverage of mixed models’ statistical properties and numerical algorithms, as well as nontraditional applications, such as regrowth curves, shapes, and images. The book features the latest topics in statistics including modeling of complex clustered or longitudinal data, modeling data with multiple sources of variation, modeling biological variety and heterogeneity, Healthy Akaike Information Criterion (HAIC), parameter multidimensionality, and statistics of image processing. Mixed Models: Theory and Applications with R, Second Edition features unique applications of mixed model methodology, as well as: Comprehensive theoretical discussions illustrated by examples and figures Over 300 exercises, end-of-section problems, updated data sets, and R subroutines Problems and extended projects requiring simulations in R intended to reinforce material Summaries of major results and general points of discussion at the end of each chapter Open problems in mixed modeling methodology, which can be used as the basis for research or PhD dissertations Ideal for graduate-level courses in mixed statistical modeling, the book is also an excellent reference for professionals in a range of fields, including cancer research, computer science, and engineering.

Finite Mixture Models

Author : Geoffrey McLachlan
Publisher : John Wiley & Sons
ISBN 13 : 047165406X
Total Pages : 419 pages
Book Rating : 4.4/5 (716 download)

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Book Synopsis Finite Mixture Models by : Geoffrey McLachlan

Download or read book Finite Mixture Models written by Geoffrey McLachlan and published by John Wiley & Sons. This book was released on 2004-03-22 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date, comprehensive account of major issues in finitemixture modeling This volume provides an up-to-date account of the theory andapplications of modeling via finite mixture distributions. With anemphasis on the applications of mixture models in both mainstreamanalysis and other areas such as unsupervised pattern recognition,speech recognition, and medical imaging, the book describes theformulations of the finite mixture approach, details itsmethodology, discusses aspects of its implementation, andillustrates its application in many common statisticalcontexts. Major issues discussed in this book include identifiabilityproblems, actual fitting of finite mixtures through use of the EMalgorithm, properties of the maximum likelihood estimators soobtained, assessment of the number of components to be used in themixture, and the applicability of asymptotic theory in providing abasis for the solutions to some of these problems. The author alsoconsiders how the EM algorithm can be scaled to handle the fittingof mixture models to very large databases, as in data miningapplications. This comprehensive, practical guide: * Provides more than 800 references-40% published since 1995 * Includes an appendix listing available mixture software * Links statistical literature with machine learning and patternrecognition literature * Contains more than 100 helpful graphs, charts, and tables Finite Mixture Models is an important resource for both applied andtheoretical statisticians as well as for researchers in the manyareas in which finite mixture models can be used to analyze data.

Handbook of Quantitative Criminology

Author : Alex R. Piquero
Publisher : Springer Science & Business Media
ISBN 13 : 0387776508
Total Pages : 787 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Handbook of Quantitative Criminology by : Alex R. Piquero

Download or read book Handbook of Quantitative Criminology written by Alex R. Piquero and published by Springer Science & Business Media. This book was released on 2009-12-16 with total page 787 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantitative criminology has certainly come a long way since I was ?rst introduced to a largely qualitative criminology some 40 years ago, when I was recruited to lead a task force on science and technology for the President’s Commission on Law Enforcement and Administration of Justice. At that time, criminology was a very limited activity, depending almost exclusively on the Uniform Crime Reports (UCR) initiated by the FBI in 1929 for measurement of crime based on victim reports to the police and on police arrests. A ty- cal mode of analysis was simple bivariate correlation. Marvin Wolfgang and colleagues were makingan importantadvancebytrackinglongitudinaldata onarrestsin Philadelphia,an in- vation that was widely appreciated. And the ?eld was very small: I remember attending my ?rst meeting of the American Society of Criminology in about 1968 in an anteroom at New York University; there were about 25–30 people in attendance, mostly sociologists with a few lawyers thrown in. That Society today has over 3,000 members, mostly now drawn from criminology which has established its own clear identity, but augmented by a wide variety of disciplines that include statisticians, economists, demographers, and even a few engineers. This Handbook provides a remarkable testimony to the growth of that ?eld. Following the maxim that “if you can’t measure it, you can’t understand it,” we have seen the early dissatisfaction with the UCR replaced by a wide variety of new approaches to measuring crime victimization and offending.

Higher-Order Growth Curves and Mixture Modeling with Mplus

Author : Kandauda A.S. Wickrama
Publisher : Routledge
ISBN 13 : 1317283929
Total Pages : 345 pages
Book Rating : 4.3/5 (172 download)

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Book Synopsis Higher-Order Growth Curves and Mixture Modeling with Mplus by : Kandauda A.S. Wickrama

Download or read book Higher-Order Growth Curves and Mixture Modeling with Mplus written by Kandauda A.S. Wickrama and published by Routledge. This book was released on 2016-04-14 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical introduction to second-order and growth mixture models using Mplus introduces simple and complex techniques through incremental steps. The authors extend latent growth curves to second-order growth curve and mixture models and then combine the two. To maximize understanding, each model is presented with basic structural equations, figures with associated syntax that highlight what the statistics mean, Mplus applications, and an interpretation of results. Examples from a variety of disciplines demonstrate the use of the models and exercises allow readers to test their understanding of the techniques. A comprehensive introduction to confirmatory factor analysis, latent growth curve modeling, and growth mixture modeling is provided so the book can be used by readers of various skill levels. The book’s datasets are available on the web. Highlights include: -Illustrative examples using Mplus 7.4 include conceptual figures, Mplus program syntax, and an interpretation of results to show readers how to carry out the analyses with actual data. -Exercises with an answer key allow readers to practice the skills they learn. -Applications to a variety of disciplines appeal to those in the behavioral, social, political, educational, occupational, business, and health sciences. -Data files for all the illustrative examples and exercises at www.routledge.com/9781138925151 allow readers to test their understanding of the concepts. -Point to Remember boxes aid in reader comprehension or provide in-depth discussions of key statistical or theoretical concepts. Part 1 introduces basic structural equation modeling (SEM) as well as first- and second-order growth curve modeling. The book opens with the basic concepts from SEM, possible extensions of conventional growth curve models, and the data and measures used throughout the book. The subsequent chapters in part 1 explain the extensions. Chapter 2 introduces conventional modeling of multidimensional panel data, including confirmatory factor analysis (CFA) and growth curve modeling, and its limitations. The logical and theoretical extension of a CFA to a second-order growth curve, known as curve-of-factors model (CFM), are explained in Chapter 3. Chapter 4 illustrates the estimation and interpretation of unconditional and conditional CFMs. Chapter 5 presents the logical and theoretical extension of a parallel process model to a second-order growth curve, known as factor-of-curves model (FCM). Chapter 6 illustrates the estimation and interpretation of unconditional and conditional FCMs. Part 2 reviews growth mixture modeling including unconditional growth mixture modeling (Ch. 7) and conditional growth mixture models (Ch. 8). How to extend second-order growth curves (curve-of-factors and factor-of-curves models) to growth mixture models is highlighted in Chapter 9. Ideal as a supplement for use in graduate courses on (advanced) structural equation, multilevel, longitudinal, or latent variable modeling, latent growth curve and mixture modeling, factor analysis, multivariate statistics, or advanced quantitative techniques (methods) taught in psychology, human development and family studies, business, education, health, and social sciences, this book’s practical approach also appeals to researchers. Prerequisites include a basic knowledge of intermediate statistics and structural equation modeling.

Methods and Applications of Longitudinal Data Analysis

Author : Xian Liu
Publisher : Elsevier
ISBN 13 : 0128014822
Total Pages : 531 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Methods and Applications of Longitudinal Data Analysis by : Xian Liu

Download or read book Methods and Applications of Longitudinal Data Analysis written by Xian Liu and published by Elsevier. This book was released on 2015-09-01 with total page 531 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methods and Applications of Longitudinal Data Analysis describes methods for the analysis of longitudinal data in the medical, biological and behavioral sciences. It introduces basic concepts and functions including a variety of regression models, and their practical applications across many areas of research. Statistical procedures featured within the text include: - descriptive methods for delineating trends over time - linear mixed regression models with both fixed and random effects - covariance pattern models on correlated errors - generalized estimating equations - nonlinear regression models for categorical repeated measurements - techniques for analyzing longitudinal data with non-ignorable missing observations Emphasis is given to applications of these methods, using substantial empirical illustrations, designed to help users of statistics better analyze and understand longitudinal data. Methods and Applications of Longitudinal Data Analysis equips both graduate students and professionals to confidently apply longitudinal data analysis to their particular discipline. It also provides a valuable reference source for applied statisticians, demographers and other quantitative methodologists. - From novice to professional: this book starts with the introduction of basic models and ends with the description of some of the most advanced models in longitudinal data analysis - Enables students to select the correct statistical methods to apply to their longitudinal data and avoid the pitfalls associated with incorrect selection - Identifies the limitations of classical repeated measures models and describes newly developed techniques, along with real-world examples.

Longitudinal Data Analysis

Author : Garrett Fitzmaurice
Publisher : CRC Press
ISBN 13 : 142001157X
Total Pages : 633 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Longitudinal Data Analysis by : Garrett Fitzmaurice

Download or read book Longitudinal Data Analysis written by Garrett Fitzmaurice and published by CRC Press. This book was released on 2008-08-11 with total page 633 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Group-Based Modeling of Development

Author : Daniel S. Nagin
Publisher : Harvard University Press
ISBN 13 : 0674041313
Total Pages : 214 pages
Book Rating : 4.6/5 (74 download)

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Book Synopsis Group-Based Modeling of Development by : Daniel S. Nagin

Download or read book Group-Based Modeling of Development written by Daniel S. Nagin and published by Harvard University Press. This book was released on 2009-07-01 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a systematic exposition of a group-based statistical method for analyzing longitudinal data in the social and behavioral sciences and in medicine. The methods can be applied to a wide range of data, such as that describing the progression of delinquency and criminality over the life course, changes in income over time, the course of a disease or physiological condition, or the evolution of the socioeconomic status of communities. Using real-world research data from longitudinal studies, the book explains and applies this method for identifying distinctive time-based progressions called developmental trajectories. Rather than assuming the existence of developmental trajectories of a specific form before statistical data analysis begins, the method allows the trajectories to emerge from the data itself. Thus, in an analysis of data on Montreal school children, it teases apart four distinct trajectories of physical aggression over the ages 6 to 15, examines predictors of these trajectories, and identifies events that may alter the trajectories. Aimed at consumers of statistical methodology, including social scientists, criminologists, psychologists, and medical researchers, the book presents the statistical theory underlying the method with a mixture of intuition and technical development.

Handbook of Mixture Analysis

Author : Sylvia Fruhwirth-Schnatter
Publisher : CRC Press
ISBN 13 : 0429508867
Total Pages : 489 pages
Book Rating : 4.4/5 (295 download)

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Book Synopsis Handbook of Mixture Analysis by : Sylvia Fruhwirth-Schnatter

Download or read book Handbook of Mixture Analysis written by Sylvia Fruhwirth-Schnatter and published by CRC Press. This book was released on 2019-01-04 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mixture models have been around for over 150 years, and they are found in many branches of statistical modelling, as a versatile and multifaceted tool. They can be applied to a wide range of data: univariate or multivariate, continuous or categorical, cross-sectional, time series, networks, and much more. Mixture analysis is a very active research topic in statistics and machine learning, with new developments in methodology and applications taking place all the time. The Handbook of Mixture Analysis is a very timely publication, presenting a broad overview of the methods and applications of this important field of research. It covers a wide array of topics, including the EM algorithm, Bayesian mixture models, model-based clustering, high-dimensional data, hidden Markov models, and applications in finance, genomics, and astronomy. Features: Provides a comprehensive overview of the methods and applications of mixture modelling and analysis Divided into three parts: Foundations and Methods; Mixture Modelling and Extensions; and Selected Applications Contains many worked examples using real data, together with computational implementation, to illustrate the methods described Includes contributions from the leading researchers in the field The Handbook of Mixture Analysis is targeted at graduate students and young researchers new to the field. It will also be an important reference for anyone working in this field, whether they are developing new methodology, or applying the models to real scientific problems.

Longitudinal and Panel Data

Author : Edward W. Frees
Publisher : Cambridge University Press
ISBN 13 : 9780521535380
Total Pages : 492 pages
Book Rating : 4.5/5 (353 download)

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Book Synopsis Longitudinal and Panel Data by : Edward W. Frees

Download or read book Longitudinal and Panel Data written by Edward W. Frees and published by Cambridge University Press. This book was released on 2004-08-16 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to foundations and applications for quantitatively oriented graduate social-science students and individual researchers.

The Oxford Handbook of Quantitative Methods, Vol. 2: Statistical Analysis

Author : Todd D. Little
Publisher : Oxford University Press
ISBN 13 : 0199934908
Total Pages : 784 pages
Book Rating : 4.1/5 (999 download)

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Book Synopsis The Oxford Handbook of Quantitative Methods, Vol. 2: Statistical Analysis by : Todd D. Little

Download or read book The Oxford Handbook of Quantitative Methods, Vol. 2: Statistical Analysis written by Todd D. Little and published by Oxford University Press. This book was released on 2013-02-01 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research today demands the application of sophisticated and powerful research tools. Fulfilling this need, The Oxford Handbook of Quantitative Methods is the complete tool box to deliver the most valid and generalizable answers to todays complex research questions. It is a one-stop source for learning and reviewing current best-practices in quantitative methods as practiced in the social, behavioral, and educational sciences. Comprising two volumes, this handbook covers a wealth of topics related to quantitative research methods. It begins with essential philosophical and ethical issues related to science and quantitative research. It then addresses core measurement topics before delving into the design of studies. Principal issues related to modern estimation and mathematical modeling are also detailed. Topics in the handbook then segway into the realm of statistical inference and modeling with chapters dedicated to classical approaches as well as modern latent variable approaches. Numerous chapters associated with longitudinal data and more specialized techniques round out this broad selection of topics. Comprehensive, authoritative, and user-friendly, this two-volume set will be an indispensable resource for serious researchers across the social, behavioral, and educational sciences.