analysis of mixed data methods applications

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Analysis Of Mixed Data

Author : Alexander R. de Leon
ISBN : 9781439884720
Genre : Mathematics
File Size : 45. 34 MB
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A comprehensive source on mixed data analysis, Analysis of Mixed Data: Methods & Applications summarizes the fundamental developments in the field. Case studies are used extensively throughout the book to illustrate interesting applications from economics, medicine and health, marketing, and genetics. Carefully edited for smooth readability and seamless transitions between chapters All chapters follow a common structure, with an introduction and a concluding summary, and include illustrative examples from real-life case studies in developmental toxicology, economics, medicine and health, marketing, and genetics An introductory chapter provides a "wide angle" introductory overview and comprehensive survey of mixed data analysis Blending theory and methodology, this book illustrates concepts via data from different disciplines. Analysis of Mixed Data: Methods & Applications traces important developments, collates basic results, presents terminology and methodologies, and gives an overview of statistical research applications. It is a valuable resource to methodologically interested as well as subject matter-motivated researchers in many disciplines.

Methods And Applications Of Longitudinal Data Analysis

Author : Xian Liu
ISBN : 9780128014820
Genre : Mathematics
File Size : 25. 49 MB
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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.

Mixed Methods Applications In Action Research

Author : Nataliya V. Ivankova
ISBN : 9781483322124
Genre : Social Science
File Size : 85. 53 MB
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Mixed Methods Applications in Action Research is a first-of-its-kind book that provides readers with the information they need to design and conduct a mixed methods action research (MMAR) study in a practical and pragmatic manner. Using a multidisciplinary focus, author Nataliya V. Ivankova provides a scholarly and applied orientation to meet the varied epistemological and professional needs of scholar practitioners. The book is applicable to broad audiences with different levels of research skills, including students learning how to conduct research in practical settings, practitioners faced with the need to address pertinent issues in their professional practices, community leaders seeking to inform policy changes, and college faculty who teach research methods and conduct funded research in collaboration with practitioner-researchers and community stakeholders. A wide variety of pedagogical features make it appropriate for use as an instructional text aimed at developing skills in designing, conducting, implementing, and reporting an action research study that integrates mixed methods. “This author has created what I believe to be a very important body of knowledge and has absolutely moved the topic in a manner that reflects current ways of thinking about research in the 21st century. The research applications presented in the textbook chapters help to make mixed method action research doable in areas that may not be reflected in previous thinking or past instructional methods for teaching research methodology.” —Juanita A. Johnson, Union Institute & University ”The scope of the material covered is terrific and the examples are very useful… I believe that it would be of great use to anyone who is considering this type of design.—Laura J. Meyer, University of Denver “Hones in on the complexities, particularities, and needs of practitioner researchers doing action research…Clearly explains integration for each mixed method type in a way I have not seen before. Figures and boxes [are] once again very valuable, organized, and clear for practitioner-researchers.” —Debby Zambo, Arizona State University

Mixed Methods Social Networks Research

Author : Silvia Dom'nguez
ISBN : 9781107027923
Genre : Political Science
File Size : 35. 5 MB
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This edited volume demonstrates the potential of mixed-methods designs for the research of social networks and the utilization of social networks for other research. Mixing methods applies to the combination and integration of qualitative and quantitative methods. In social network research, mixing methods also applies to the combination of structural and actor-oriented approaches. The volume provides readers with methodological concepts to guide mixed-method network studies with precise research designs and methods to investigate social networks of various sorts. Each chapter describes the research design used and discusses the strengths of the methods for that particular field and for specific outcomes.

Nonparametric Regression Methods For Longitudinal Data Analysis

Author : Hulin Wu
ISBN : 9780470009666
Genre : Mathematics
File Size : 52. 42 MB
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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.

Handbook Of Mixed Membership Models And Their Applications

Author : Edoardo M. Airoldi
ISBN : 9781466504080
Genre : Computers
File Size : 85. 95 MB
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In response to scientific needs for more diverse and structured explanations of statistical data, researchers have discovered how to model individual data points as belonging to multiple groups. Handbook of Mixed Membership Models and Their Applications shows you how to use these flexible modeling tools to uncover hidden patterns in modern high-dimensional multivariate data. It explores the use of the models in various application settings, including survey data, population genetics, text analysis, image processing and annotation, and molecular biology. Through examples using real data sets, you’ll discover how to characterize complex multivariate data in: Studies involving genetic databases Patterns in the progression of diseases and disabilities Combinations of topics covered by text documents Political ideology or electorate voting patterns Heterogeneous relationships in networks, and much more The handbook spans more than 20 years of the editors’ and contributors’ statistical work in the field. Top researchers compare partial and mixed membership models, explain how to interpret mixed membership, delve into factor analysis, and describe nonparametric mixed membership models. They also present extensions of the mixed membership model for text analysis, sequence and rank data, and network data as well as semi-supervised mixed membership models.

Generalized Linear Mixed Models

Author : Walter W. Stroup
ISBN : 9781439815137
Genre : Mathematics
File Size : 22. 47 MB
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Generalized Linear Mixed Models: Modern Concepts, Methods and Applications presents an introduction to linear modeling using the generalized linear mixed model (GLMM) as an overarching conceptual framework. For readers new to linear models, the book helps them see the big picture. It shows how linear models fit with the rest of the core statistics curriculum and points out the major issues that statistical modelers must consider. Along with describing common applications of GLMMs, the text introduces the essential theory and main methodology associated with linear models that accommodate random model effects and non-Gaussian data. Unlike traditional linear model textbooks that focus on normally distributed data, this one adopts a generalized mixed model approach throughout: data for linear modeling need not be normally distributed and effects may be fixed or random. With numerous examples using SAS® PROC GLIMMIX, this book is ideal for graduate students in statistics, statistics professionals seeking to update their knowledge, and researchers new to the generalized linear model thought process. It focuses on data-driven processes and provides context for extending traditional linear model thinking to generalized linear mixed modeling. See Professor Stroup discuss the book.

Mixed Models

Author : Eugene Demidenko
ISBN : 0471726133
Genre : Mathematics
File Size : 37. 33 MB
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Modeling Intraindividual Variability With Repeated Measures Data

Author : Scott L. Hershberger
ISBN : 9781135673215
Genre : Psychology
File Size : 26. 84 MB
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This book examines how individuals behave across time and to what degree that behavior changes, fluctuates, or remains stable. It features the most current methods on modeling repeated measures data as reported by a distinguished group of experts in the field. The goal is to make the latest techniques used to assess intraindividual variability accessible to a wide range of researchers. Each chapter is written in a "user-friendly" style such that even the "novice" data analyst can easily apply the techniques. Each chapter features: a minimum discussion of mathematical detail; an empirical example applying the technique; and a discussion of the software related to that technique. Content highlights include analysis of mixed, multi-level, structural equation, and categorical data models. It is ideal for researchers, professionals, and students working with repeated measures data from the social and behavioral sciences, business, or biological sciences.

Advanced Data Mining And Applications

Author : Jinyan Li
ISBN : 9783319495866
Genre : Computers
File Size : 76. 35 MB
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This book constitutes the proceedings of the 12th International Conference on Advanced Data Mining and Applications, ADMA 2016, held in Gold Coast, Australia, in December 2016. The 70 papers presented in this volume were carefully reviewed and selected from 105 submissions. The selected papers covered a wide variety of important topics in the area of data mining, including parallel and distributed data mining algorithms, mining on data streams, graph mining, spatial data mining, multimedia data mining, Web mining, the Internet of Things, health informatics, and biomedical data mining.

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