analysis of mixed data methods applications

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Analysis Of Mixed Data

Author : Alexander R. de Leon
ISBN : 9781439884713
Genre : Mathematics
File Size : 46. 87 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 : 29. 25 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 : 68. 92 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.

Integrating Analyses In Mixed Methods Research

Author : Patricia Bazeley
ISBN : 9781526417183
Genre : Reference
File Size : 57. 72 MB
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Integrating Analyses in Mixed Methods Research goes beyond mixed methods research design and data collection, providing a pragmatic discussion of the challenges of effectively integrating data to facilitate a more comprehensive and rigorous level of analysis. Showcasing a range of strategies for integrating different sources and forms of data as well as different approaches in analysis, it helps you plan, conduct, and disseminate complex analyses with confidence. Key techniques include: Building an integrative framework Analysing sequential, complementary and comparative data Identifying patterns and contrasts in linked data Categorizing, counting, and blending mixed data Managing dissonance and divergence Transforming analysis into warranted assertions With clear steps that can be tailored to any project, this book is perfect for students and researchers undertaking their own mixed methods research.

Sage Handbook Of Mixed Methods In Social Behavioral Research

Author : Abbas Tashakkori
ISBN : 9781412972666
Genre : Psychology
File Size : 73. 91 MB
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Rev. ed. of: Handbook of mixed methods in social & behavioral research.

Designing And Conducting Mixed Methods Research

Author : John W. Creswell
ISBN : 9781412975179
Genre : Mathematics
File Size : 55. 6 MB
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'Designing and Conducting Mixed Methods Research' offers a practical, how-to guide for designing a mixed methods study. The text incorporates activities and exercises for classroom use or for use by the researcher in preparing designs.

Analysis Of Variance For Random Models Volume 2 Unbalanced Data

Author : Hardeo Sahai
ISBN : 9780817644253
Genre : Mathematics
File Size : 78. 42 MB
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Systematic treatment of the commonly employed crossed and nested classification models used in analysis of variance designs with a detailed and thorough discussion of certain random effects models not commonly found in texts at the introductory or intermediate level. It also includes numerical examples to analyze data from a wide variety of disciplines as well as any worked examples containing computer outputs from standard software packages such as SAS, SPSS, and BMDP for each numerical example.

Nonlinear Principal Component Analysis And Its Applications

Author : Yuichi Mori
ISBN : 9789811001598
Genre : Mathematics
File Size : 40. 52 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.

Nonparametric Regression Methods For Longitudinal Data Analysis

Author : Hulin Wu
ISBN : 9780470009666
Genre : Mathematics
File Size : 76. 67 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 Research Methods And Applications In Heterodox Economics

Author : The Late Frederic S. Lee
ISBN : 9781782548461
Genre : BUSINESS & ECONOMICS
File Size : 57. 62 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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