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 : 77. 93 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 : 33. 56 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 : 9781452220031
Genre : Social Science
File Size : 44. 23 MB
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Focusing throughout on the integrated use of quantitative and qualitative methods, the book includes illustrative examples, featured SAGE journal articles, scripts, templates, and outlines to help readers master each step of the process. A wide range of reports are illustrated, including a community-oriented report, a professional research-based manuscript, and a dissertation research study. The final chapter discusses how the knowledge generated through a Mixed Methods Action Research (MMAR) study can lead to community action.

Modeling Intraindividual Variability With Repeated Measures Data

Author : Scott L. Hershberger
ISBN : 9781135673215
Genre : Psychology
File Size : 28. 99 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.

Nonparametric Regression Methods For Longitudinal Data Analysis

Author : Hulin Wu
ISBN : 9780470009666
Genre : Mathematics
File Size : 86. 37 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.

Sage Handbook Of Mixed Methods In Social Behavioral Research

Author : Abbas Tashakkori
ISBN : 9781412972666
Genre : Psychology
File Size : 32. 27 MB
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Rev. ed. of: Handbook of mixed methods in social & behavioral research.

Advances In Mixed Methods Research

Author : Manfred Max Bergman
ISBN : 9781446241219
Genre : Social Science
File Size : 44. 50 MB
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Advances in Mixed Methods Research provides an essential introduction to the fast-growing field of mixed methods research. Bergman's book examines the current state of mixed-methods research, exploring exciting new ways of conceptualizing and conducting empirical research in the social and health sciences. Contributions from the world's leading experts in qualitative, quantitative, and mixed methods approaches are brought together, clearing the way for a more constructive approach to social research. These contributions cover the main practical and methodological issues and include a number of different visions of what mixed methods research is. The discussion also covers the use of mixed methods in a diverse range of fields, including sociology, education, politics, psychology, computational science and methodology. This book represents an important contribution to the ongoing debate surrounding the use of mixed methods in the social sciences and health research, and presents a convincing argument that the conventional, paradigmatic view of qualitative and quantitative research is outdated and in need of replacement. It will be essential reading for anyone actively engaged in qualitative, quantitative and mixed methods research and for students of social research methods. Manfred Max Bergman is Chair of Methodology and Political Sociology at the University of Basel.

Methods And Applications Of Linear Models

Author : Ronald R. Hocking
ISBN : 9781118593028
Genre : Mathematics
File Size : 84. 54 MB
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Praise for the Second Edition "An essential desktop reference book . . . it should definitely be on your bookshelf." —Technometrics A thoroughly updated book, Methods and Applications of Linear Models: Regression and the Analysis of Variance, Third Edition features innovative approaches to understanding and working with models and theory of linear regression. The Third Edition provides readers with the necessary theoretical concepts, which are presented using intuitive ideas rather than complicated proofs, to describe the inference that is appropriate for the methods being discussed. The book presents a unique discussion that combines coverage of mathematical theory of linear models with analysis of variance models, providing readers with a comprehensive understanding of both the theoretical and technical aspects of linear models. With a new focus on fixed effects models, Methods and Applications of Linear Models: Regression and the Analysis of Variance, Third Edition also features: Newly added topics including least squares, the cell means model, and graphical inspection of data in the AVE method Frequent conceptual and numerical examples for clarifying the statistical analyses and demonstrating potential pitfalls Graphics and computations developed using JMP® software to accompany the concepts and techniques presented Numerous exercises presented to test readers and deepen their understanding of the material An ideal book for courses on linear models and linear regression at the undergraduate and graduate levels, the Third Edition of Methods and Applications of Linear Models: Regression and the Analysis of Variance is also a valuable reference for applied statisticians and researchers who utilize linear model methodology.

Nonlinear Principal Component Analysis And Its Applications

Author : Yuichi Mori
ISBN : 9789811001598
Genre : Mathematics
File Size : 51. 51 MB
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This book expounds the principle and related applications of nonlinear principal component analysis (PCA), which is useful method to analyze mixed measurement levels data. In the part dealing with the principle, after a brief introduction of ordinary PCA, a PCA for categorical data (nominal and ordinal) is introduced as nonlinear PCA, in which an optimal scaling technique is used to quantify the categorical variables. The alternating least squares (ALS) is the main algorithm in the method. Multiple correspondence analysis (MCA), a special case of nonlinear PCA, is also introduced. All formulations in these methods are integrated in the same manner as matrix operations. Because any measurement levels data can be treated consistently as numerical data and ALS is a very powerful tool for estimations, the methods can be utilized in a variety of fields such as biometrics, econometrics, psychometrics, and sociology. In the applications part of the book, four applications are introduced: variable selection for mixed measurement levels data, sparse MCA, joint dimension reduction and clustering methods for categorical data, and acceleration of ALS computation. The variable selection methods in PCA that originally were developed for numerical data can be applied to any types of measurement levels by using nonlinear PCA. Sparseness and joint dimension reduction and clustering for nonlinear data, the results of recent studies, are extensions obtained by the same matrix operations in nonlinear PCA. Finally, an acceleration algorithm is proposed to reduce the problem of computational cost in the ALS iteration in nonlinear multivariate methods. This book thus presents the usefulness of nonlinear PCA which can be applied to different measurement levels data in diverse fields. As well, it covers the latest topics including the extension of the traditional statistical method, newly proposed nonlinear methods, and computational efficiency in the methods.

Handbook Of Research Methods And Applications In Heterodox Economics

Author : The Late Frederic S. Lee
ISBN : 9781782548461
Genre : BUSINESS & ECONOMICS
File Size : 77. 58 MB
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Despite the important methodological critiques of the mainstream offered by heterodox economics, the dominant research method taught in heterodox programmes remains econometrics. This compelling Handbook provides a comprehensive introduction to a range of alternative research methods, invaluable for analysing the data prominent in heterodox studies. Providing a solid basis for a mixed methods approach to economic investigations, the expertly crafted contributions are split into three distinct sections: philosophical foundation and research strategy, research methods and data collection, and applications. Introductions to a host of invaluable methods such as survey, historical, ethnographic, experimental and mixed approaches, together with factor, cluster, complex and social network analytics, are complemented by descriptions of applications in practice. Practical and expansive, this Handbook is highly pertinent for students and scholars of economics, particularly those dedicated to heterodox approaches, as it provides a solid reference for mixed methods not available in mainstream economics research methods courses.

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