Analysis Of Mixed Data
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Analysis Of Mixed Data
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Author : Alexander R. de Leon
language : en
Publisher: CRC Press
Release Date : 2013-01-16
Analysis Of Mixed Data written by Alexander R. de Leon and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-16 with Mathematics categories.
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.
Integrating Analyses In Mixed Methods Research
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Author : Patricia Bazeley
language : en
Publisher: SAGE
Release Date : 2017-09-25
Integrating Analyses In Mixed Methods Research written by Patricia Bazeley and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-25 with Social Science categories.
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.
Analysis Of Mixed Data
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Author : Alexander R. de Leon
language : en
Publisher: CRC Press
Release Date : 2013-01-16
Analysis Of Mixed Data written by Alexander R. de Leon and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-16 with Mathematics categories.
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
Multiple Factor Analysis By Example Using R
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Author : Jérôme Pagès
language : en
Publisher: CRC Press
Release Date : 2014-11-20
Multiple Factor Analysis By Example Using R written by Jérôme Pagès and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-20 with Mathematics categories.
Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also includes examples of applications and details of how to implement MFA using an R package (FactoMineR). The first two chapters cover the basic factorial analysis methods of principal component analysis (PCA) and multiple correspondence analysis (MCA). The next chapter discusses factor analysis for mixed data (FAMD), a little-known method for simultaneously analyzing quantitative and qualitative variables without group distinction. Focusing on MFA, subsequent chapters examine the key points of MFA in the context of quantitative variables as well as qualitative and mixed data. The author also compares MFA and Procrustes analysis and presents a natural extension of MFA: hierarchical MFA (HMFA). The final chapter explores several elements of matrix calculation and metric spaces used in the book.
Practical Guide To Principal Component Methods In R
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Author : Alboukadel KASSAMBARA
language : en
Publisher: STHDA
Release Date : 2017-08-23
Practical Guide To Principal Component Methods In R written by Alboukadel KASSAMBARA and has been published by STHDA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-23 with Education categories.
Although there are several good books on principal component methods (PCMs) and related topics, we felt that many of them are either too theoretical or too advanced. This book provides a solid practical guidance to summarize, visualize and interpret the most important information in a large multivariate data sets, using principal component methods in R. The visualization is based on the factoextra R package that we developed for creating easily beautiful ggplot2-based graphs from the output of PCMs. This book contains 4 parts. Part I provides a quick introduction to R and presents the key features of FactoMineR and factoextra. Part II describes classical principal component methods to analyze data sets containing, predominantly, either continuous or categorical variables. These methods include: Principal Component Analysis (PCA, for continuous variables), simple correspondence analysis (CA, for large contingency tables formed by two categorical variables) and Multiple CA (MCA, for a data set with more than 2 categorical variables). In Part III, you'll learn advanced methods for analyzing a data set containing a mix of variables (continuous and categorical) structured or not into groups: Factor Analysis of Mixed Data (FAMD) and Multiple Factor Analysis (MFA). Part IV covers hierarchical clustering on principal components (HCPC), which is useful for performing clustering with a data set containing only categorical variables or with a mixed data of categorical and continuous variables.
Data Analysis Using Sas Enterprise Guide
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Author : Lawrence S. Meyers
language : en
Publisher: Cambridge University Press
Release Date : 2009-08-17
Data Analysis Using Sas Enterprise Guide written by Lawrence S. Meyers and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-08-17 with Business & Economics categories.
This book presents the basic procedures for utilizing SAS Enterprise Guide to analyze statistical data. SAS Enterprise Guide is a graphical user interface (point and click) to the main SAS application. Each chapter contains a brief conceptual overview and then guides the reader through concrete step-by-step examples to complete the analyses. The eleven sections of the book cover a wide range of statistical procedures including descriptive statistics, correlation and simple regression, t tests, one-way chi square, data transformations, multiple regression, analysis of variance, analysis of covariance, multivariate analysis of variance, factor analysis, and canonical correlation analysis. Designed to be used either as a stand-alone resource or as an accompaniment to a statistics course, the book offers a smooth path to statistical analysis with SAS Enterprise Guide for advanced undergraduate and beginning graduate students, as well as professionals in psychology, education, business, health, social work, sociology, and many other fields.
The Analysis Of Variance
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Author : Hardeo Sahai
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
The Analysis Of Variance written by Hardeo Sahai and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
The analysis of variance (ANOYA) models have become one of the most widely used tools of modern statistics for analyzing multifactor data. The ANOYA models provide versatile statistical tools for studying the relationship between a dependent variable and one or more independent variables. The ANOYA mod els are employed to determine whether different variables interact and which factors or factor combinations are most important. They are appealing because they provide a conceptually simple technique for investigating statistical rela tionships among different independent variables known as factors. Currently there are several texts and monographs available on the sub ject. However, some of them such as those of Scheffe (1959) and Fisher and McDonald (1978), are written for mathematically advanced readers, requiring a good background in calculus, matrix algebra, and statistical theory; whereas others such as Guenther (1964), Huitson (1971), and Dunn and Clark (1987), although they assume only a background in elementary algebra and statistics, treat the subject somewhat scantily and provide only a superficial discussion of the random and mixed effects analysis of variance.
Mixed Methods Social Network Analysis
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Author : Dominik E. Froehlich
language : en
Publisher: Routledge
Release Date : 2019-12-09
Mixed Methods Social Network Analysis written by Dominik E. Froehlich and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-09 with Computers categories.
Mixed Methods Social Network Analysis brings together diverse perspectives from 42 international experts on how to design, implement, and evaluate mixed methods social network analysis (MMSNA). There is an increased recognition that social networks can be important catalysts for change and transformation. This edited book from leading experts in mixed methods and social network analysis describes how researchers can conceptualize, develop, mix, and intersect diverse approaches, concepts, and tools. In doing so, they can improve their understanding and insights into the complex change processes in social networks. Section 1 includes eight chapters that reflect on "Why should we do MMSNA?", providing a clear map of MMSNA research to date and why to consider MMSNA. In Section 2 the remaining 11 chapters are dedicated to the question "How do I do MMSNA?", illustrating how concentric circles, learning analytics, qualitative structured approaches, relational event modeling, and other approaches can empower researchers. This book shows that mixing qualitative and quantitative approaches to social network analysis can empower people to understand the complexities of change in networks and relations between people. It shows how mixed analysis can be applied to a wide range of data generated by diverse global communities: American school children, Belgian teachers, Dutch medical professionals, Finnish consultants, French school children, and Swedish right-wing social media users, amongst others. It will be of great interest to researchers and postgraduate students in education and social sciences and mixed methods scholars.
Mixed Mode Official Surveys
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Author : Barry Schouten
language : en
Publisher: CRC Press
Release Date : 2021-09-27
Mixed Mode Official Surveys written by Barry Schouten and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-27 with Mathematics categories.
Mixed-mode surveys have become a standard at many statistical institutes. However, the introduction of multiple modes in one design goes with challenges to both methodology and logistics. Mode-specific representation and measurement differences become explicit and demand for solutions in data collection design, questionnaire design, and estimation. This is especially true when surveys are repeated and are input to long time series of official statistics. So how can statistical institutes deal with such changes? What are the origins of mode-specific error? And how can they be dealt with? In this book, the authors provide answers to these questions, and much more. Features Concise introduction to all the key elements of mixed-mode survey design and analysis Realistic official statistics examples from three general population surveys Suitable for survey managers and survey statisticians alike An overview of mode-specific representation and measurement errors and how to avoid, reduce and adjust them.
Selecting The Right Analyses For Your Data
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Author : W. Paul Vogt
language : en
Publisher: Guilford Publications
Release Date : 2014-05-19
Selecting The Right Analyses For Your Data written by W. Paul Vogt and has been published by Guilford Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-19 with Social Science categories.
"What are the most effective methods to code and analyze data for a particular study? This thoughtful and engaging book reviews the selection criteria for coding and analyzing any set of data--whether qualitative, quantitative, mixed, or visual. The authors systematically explain when to use verbal, numerical, graphic, or combined codes, and when to use qualitative, quantitative, graphic, or mixed-methods modes of analysis. Chapters on each topic are organized so that researchers can read them sequentially or can easily "flip and find" answers to specific questions. Nontechnical discussions of cutting-edge approaches--illustrated with real-world examples--emphasize how to choose (rather than how to implement) the various analyses. The book shows how using the right analysis methods leads to more justifiable conclusions and more persuasive presentations of research results. Useful features for teaching or self-study: *Chapter-opening preview boxes that highlight useful topics addressed. *End-of-chapter summary tables recapping the 'dos and don'ts' and advantages and disadvantages of each analytic technique. *Annotated suggestions for further reading and technical resources on each topic. Subject Areas/Keywords: analyses, coding, combined methods, data analysis, data collection, dissertation, graphical, interpretation, mixed methods, qualitative, quantitative, research analysis, research designs, research methods, social sciences, thesis, visual Audience: Researchers, instructors, and graduate students in a range of disciplines, including psychology, education, social work, sociology, health, and management; administrators and managers who need to make data-driven decisions"--