Analysis Of Integrated Data
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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 Integrated And Cointegrated Time Series With R
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Author : Bernhard Pfaff
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-09-03
Analysis Of Integrated And Cointegrated Time Series With R written by Bernhard Pfaff 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 2008-09-03 with Business & Economics categories.
This book is designed for self study. The reader can apply the theoretical concepts directly within R by following the examples.
Analysis Of Integrated Data
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Author : Li-Chun Zhang
language : en
Publisher: CRC Press
Release Date : 2019-04-18
Analysis Of Integrated Data written by Li-Chun Zhang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-18 with Mathematics categories.
The advent of "Big Data" has brought with it a rapid diversification of data sources, requiring analysis that accounts for the fact that these data have often been generated and recorded for different reasons. Data integration involves combining data residing in different sources to enable statistical inference, or to generate new statistical data for purposes that cannot be served by each source on its own. This can yield significant gains for scientific as well as commercial investigations. However, valid analysis of such data should allow for the additional uncertainty due to entity ambiguity, whenever it is not possible to state with certainty that the integrated source is the target population of interest. Analysis of Integrated Data aims to provide a solid theoretical basis for this statistical analysis in three generic settings of entity ambiguity: statistical analysis of linked datasets that may contain linkage errors; datasets created by a data fusion process, where joint statistical information is simulated using the information in marginal data from non-overlapping sources; and estimation of target population size when target units are either partially or erroneously covered in each source. Covers a range of topics under an overarching perspective of data integration. Focuses on statistical uncertainty and inference issues arising from entity ambiguity. Features state of the art methods for analysis of integrated data. Identifies the important themes that will define future research and teaching in the statistical analysis of integrated data. Analysis of Integrated Data is aimed primarily at researchers and methodologists interested in statistical methods for data from multiple sources, with a focus on data analysts in the social sciences, and in the public and private sectors.
Introduction To The Theory And Application Of Data Envelopment Analysis
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Author : Emmanuel Thanassoulis
language : en
Publisher: Springer Science & Business Media
Release Date : 2001-07-31
Introduction To The Theory And Application Of Data Envelopment Analysis written by Emmanuel Thanassoulis 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 2001-07-31 with Business & Economics categories.
The book aims to introduce the reader to DEA in the most accessible manner possible. It is specifically aimed at those who have had no prior exposure to DEA and wish to learn its essentials, how it works, its key uses, and the mechanics of using it. The latter will include using DEA software. Students on degree or training courses will find the book especially helpful. The same is true of practitioners engaging in comparative efficiency assessments and performance management within their organisation. Examples are used throughout the book to help the reader consolidate the concepts covered.
Introduction To Time Series Analysis
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Author : Mark Pickup
language : en
Publisher: SAGE Publications
Release Date : 2014-10-15
Introduction To Time Series Analysis written by Mark Pickup and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-15 with Social Science categories.
Introducing time series methods and their application in social science research, this practical guide to time series models is the first in the field written for a non-econometrics audience. Giving readers the tools they need to apply models to their own research, Introduction to Time Series Analysis, by Mark Pickup, demonstrates the use of—and the assumptions underlying—common models of time series data including finite distributed lag; autoregressive distributed lag; moving average; differenced data; and GARCH, ARMA, ARIMA, and error correction models. “This volume does an excellent job of introducing modern time series analysis to social scientists who are already familiar with basic statistics and the general linear model.” —William G. Jacoby, Michigan State University
Big Data In Omics And Imaging
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Author : Momiao Xiong
language : en
Publisher: CRC Press
Release Date : 2018-06-14
Big Data In Omics And Imaging written by Momiao Xiong and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-14 with Mathematics categories.
Big Data in Omics and Imaging: Integrated Analysis and Causal Inference addresses the recent development of integrated genomic, epigenomic and imaging data analysis and causal inference in big data era. Despite significant progress in dissecting the genetic architecture of complex diseases by genome-wide association studies (GWAS), genome-wide expression studies (GWES), and epigenome-wide association studies (EWAS), the overall contribution of the new identified genetic variants is small and a large fraction of genetic variants is still hidden. Understanding the etiology and causal chain of mechanism underlying complex diseases remains elusive. It is time to bring big data, machine learning and causal revolution to developing a new generation of genetic analysis for shifting the current paradigm of genetic analysis from shallow association analysis to deep causal inference and from genetic analysis alone to integrated omics and imaging data analysis for unraveling the mechanism of complex diseases. FEATURES Provides a natural extension and companion volume to Big Data in Omic and Imaging: Association Analysis, but can be read independently. Introduce causal inference theory to genomic, epigenomic and imaging data analysis Develop novel statistics for genome-wide causation studies and epigenome-wide causation studies. Bridge the gap between the traditional association analysis and modern causation analysis Use combinatorial optimization methods and various causal models as a general framework for inferring multilevel omic and image causal networks Present statistical methods and computational algorithms for searching causal paths from genetic variant to disease Develop causal machine learning methods integrating causal inference and machine learning Develop statistics for testing significant difference in directed edge, path, and graphs, and for assessing causal relationships between two networks The book is designed for graduate students and researchers in genomics, epigenomics, medical image, bioinformatics, and data science. Topics covered are: mathematical formulation of causal inference, information geometry for causal inference, topology group and Haar measure, additive noise models, distance correlation, multivariate causal inference and causal networks, dynamic causal networks, multivariate and functional structural equation models, mixed structural equation models, causal inference with confounders, integer programming, deep learning and differential equations for wearable computing, genetic analysis of function-valued traits, RNA-seq data analysis, causal networks for genetic methylation analysis, gene expression and methylation deconvolution, cell –specific causal networks, deep learning for image segmentation and image analysis, imaging and genomic data analysis, integrated multilevel causal genomic, epigenomic and imaging data analysis.
The Oxford Handbook Of Multimethod And Mixed Methods Research Inquiry
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Author : Sharlene Nagy Hesse-Biber
language : en
Publisher: Oxford University Press
Release Date : 2015-06-04
The Oxford Handbook Of Multimethod And Mixed Methods Research Inquiry written by Sharlene Nagy Hesse-Biber and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-04 with Psychology categories.
Offering a variety of innovative methods and tools, The Oxford Handbook of Multimethod and Mixed Methods Research Inquiry provides the most comprehensive and up-to-date presentation on multi- and mixed-methods research available. Written in clear and concise language by leading scholars in the field, it enhances and disrupts traditional ways of asking and addressing complex research questions. Topics include an overview of theory, paradigms, and scientific inquiry; a guide to conducting a multi- and mixed-methods research study from start to finish; current uses of multi- and mixed-methods research across academic disciplines and research fields; the latest technologies and how they can be incorporated into study design; and a presentation of multiple perspectives on the key remaining debates. Each chapter in the volume is structured to include state-of-the-art research examples that cross a range of disciplines and interdisciplinary research settings. In addition, the Handbook offers multiple quantitative and qualitative theoretical and interdisciplinary visions and praxis. Researchers, faculty, graduate students, and policy makers will appreciate the exceptional, timely, and critical coverage in this Handbook, which deftly addresses the interdisciplinary and complex questions that a diverse set of research communities are facing today.
Business Intelligence Guidebook
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Author : Rick Sherman
language : en
Publisher: Newnes
Release Date : 2014-11-04
Business Intelligence Guidebook written by Rick Sherman and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-04 with Computers categories.
Between the high-level concepts of business intelligence and the nitty-gritty instructions for using vendors' tools lies the essential, yet poorly-understood layer of architecture, design and process. Without this knowledge, Big Data is belittled – projects flounder, are late and go over budget. Business Intelligence Guidebook: From Data Integration to Analytics shines a bright light on an often neglected topic, arming you with the knowledge you need to design rock-solid business intelligence and data integration processes. Practicing consultant and adjunct BI professor Rick Sherman takes the guesswork out of creating systems that are cost-effective, reusable and essential for transforming raw data into valuable information for business decision-makers. After reading this book, you will be able to design the overall architecture for functioning business intelligence systems with the supporting data warehousing and data-integration applications. You will have the information you need to get a project launched, developed, managed and delivered on time and on budget – turning the deluge of data into actionable information that fuels business knowledge. Finally, you'll give your career a boost by demonstrating an essential knowledge that puts corporate BI projects on a fast-track to success. - Provides practical guidelines for building successful BI, DW and data integration solutions. - Explains underlying BI, DW and data integration design, architecture and processes in clear, accessible language. - Includes the complete project development lifecycle that can be applied at large enterprises as well as at small to medium-sized businesses - Describes best practices and pragmatic approaches so readers can put them into action. - Companion website includes templates and examples, further discussion of key topics, instructor materials, and references to trusted industry sources.
Interactive Visual Data Analysis
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Author : Christian Tominski
language : en
Publisher: AK Peters Visualization Series
Release Date : 2020
Interactive Visual Data Analysis written by Christian Tominski and has been published by AK Peters Visualization Series this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with TECHNOLOGY & ENGINEERING categories.
In the age of big data, being able to make sense of data is an important key to success. Interactive Visual Data Analysis advocates the synthesis of visualization, interaction, and automatic computation to facilitate insight generation and knowledge crystallization from large and complex data. The book provides a systematic and comprehensive overview of visual, interactive, and analytical methods. It introduces criteria for designing interactive visual data analysis solutions, discusses factors influencing the design, and examines the involved processes. The reader is made familiar with the basics of visual encoding and gets to know numerous visualization techniques for multivariate data, temporal data, geo-spatial data, and graph data. A dedicated chapter introduces general concepts for interacting with visualizations and illustrates how modern interaction technology can facilitate the visual data analysis in many ways. Addressing today's large and complex data, the book covers relevant automatic analytical computations to support the visual data analysis. The book also sheds light on advanced concepts for visualization in multi-display environments, user guidance during the data analysis, and progressive visual data analysis. The authors present a top-down perspective on interactive visual data analysis with a focus on concise and clean terminology. Many real-world examples and rich illustrations make the book accessible to a broad interdisciplinary audience from students, to experts in the field, to practitioners in data-intensive application domains. Features: Dedicated to the synthesis of visual, interactive, and analysis methods Systematic top-down view on visualization, interaction, and automatic analysis Broad coverage of fundamental and advanced visualization techniques Comprehensive chapter on interacting with visual representations Extensive integration of automatic computational methods Accessible portrayal of cutting-edge visual analytics technology For more information, you can also visit the author website, where the book's figures will be made available under the CC BY Open Access license: https: //ivda-book.de/
Synthesis Of Best Practices For The Development Of An Integrated Data And Information Management Approach
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Author : Teresa M. Adams
language : en
Publisher:
Release Date : 2008
Synthesis Of Best Practices For The Development Of An Integrated Data And Information Management Approach written by Teresa M. Adams and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Electronic data processing categories.