Analysis Of Incomplete Multivariate Data
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Analysis Of Incomplete Multivariate Data
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Author : J.L. Schafer
language : en
Publisher: CRC Press
Release Date : 1997-08-01
Analysis Of Incomplete Multivariate Data written by J.L. Schafer and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-08-01 with Mathematics categories.
The last two decades have seen enormous developments in statistical methods for incomplete data. The EM algorithm and its extensions, multiple imputation, and Markov Chain Monte Carlo provide a set of flexible and reliable tools from inference in large classes of missing-data problems. Yet, in practical terms, those developments have had surprisingly little impact on the way most data analysts handle missing values on a routine basis. Analysis of Incomplete Multivariate Data helps bridge the gap between theory and practice, making these missing-data tools accessible to a broad audience. It presents a unified, Bayesian approach to the analysis of incomplete multivariate data, covering datasets in which the variables are continuous, categorical, or both. The focus is applied, where necessary, to help readers thoroughly understand the statistical properties of those methods, and the behavior of the accompanying algorithms. All techniques are illustrated with real data examples, with extended discussion and practical advice. All of the algorithms described in this book have been implemented by the author for general use in the statistical languages S and S Plus. The software is available free of charge on the Internet.
Applied Missing Data Analysis
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Author : Craig K. Enders
language : en
Publisher: Guilford Press
Release Date : 2010-04-23
Applied Missing Data Analysis written by Craig K. Enders and has been published by Guilford Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-04-23 with Psychology categories.
Walking readers step by step through complex concepts, this book translates missing data techniques into something that applied researchers and graduate students can understand and utilize in their own research. Enders explains the rationale and procedural details for maximum likelihood estimation, Bayesian estimation, multiple imputation, and models for handling missing not at random (MNAR) data. Easy-to-follow examples and small simulated data sets illustrate the techniques and clarify the underlying principles. The companion website includes data files and syntax for the examples in the book as well as up-to-date information on software. The book is accessible to substantive researchers while providing a level of detail that will satisfy quantitative specialists. This book will appeal to researchers and graduate students in psychology, education, management, family studies, public health, sociology, and political science. It will also serve as a supplemental text for doctoral-level courses or seminars in advanced quantitative methods, survey analysis, longitudinal data analysis, and multilevel modeling, and as a primary text for doctoral-level courses or seminars in missing data.
Multiple Imputation And Its Application
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Author : James Carpenter
language : en
Publisher: John Wiley & Sons
Release Date : 2012-12-21
Multiple Imputation And Its Application written by James Carpenter and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-21 with Medical categories.
A practical guide to analysing partially observeddata. Collecting, analysing and drawing inferences from data iscentral to research in the medical and social sciences.Unfortunately, it is rarely possible to collect all the intendeddata. The literature on inference from the resultingincomplete data is now huge, and continues to grow both asmethods are developed for large and complex data structures, and asincreasing computer power and suitable software enable researchersto apply these methods. This book focuses on a particular statistical method foranalysing and drawing inferences from incomplete data, calledMultiple Imputation (MI). MI is attractive because it is bothpractical and widely applicable. The authors aim is to clarify theissues raised by missing data, describing the rationale for MI, therelationship between the various imputation models and associatedalgorithms and its application to increasingly complex datastructures. Multiple Imputation and its Application: Discusses the issues raised by the analysis of partiallyobserved data, and the assumptions on which analyses rest. Presents a practical guide to the issues to consider whenanalysing incomplete data from both observational studies andrandomized trials. Provides a detailed discussion of the practical use of MI withreal-world examples drawn from medical and social statistics. Explores handling non-linear relationships and interactionswith multiple imputation, survival analysis, multilevel multipleimputation, sensitivity analysis via multiple imputation, usingnon-response weights with multiple imputation and doubly robustmultiple imputation. Multiple Imputation and its Application is aimed atquantitative researchers and students in the medical and socialsciences with the aim of clarifying the issues raised by theanalysis of incomplete data data, outlining the rationale for MIand describing how to consider and address the issues that arise inits application.
Multivariate Data Analysis
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Author : Barbara Bund
language : en
Publisher: McGraw-Hill/Irwin
Release Date : 1983
Multivariate Data Analysis written by Barbara Bund and has been published by McGraw-Hill/Irwin this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983 with Mathematics categories.
Multi And Megavariate Data Analysis Basic Principles And Applications
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Author : L. Eriksson
language : en
Publisher: Umetrics Academy
Release Date : 2013-07-01
Multi And Megavariate Data Analysis Basic Principles And Applications written by L. Eriksson and has been published by Umetrics Academy this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-01 with Mathematics categories.
To understand the world around us, as well as ourselves, we need to measure many things, many variables, many properties of the systems and processes we investigate. Hence, data collected in science, technology, and almost everywhere else are multivariate, a data table with multiple variables measured on multiple observations (cases, samples, items, process time points, experiments). This book describes a remarkably simple minimalistic and practical approach to the analysis of data tables (multivariate data). The approach is based on projection methods, which are PCA (principal components analysis), and PLS (projection to latent structures) and the book shows how this works in science and technology for a wide variety of applications. In particular, it is shown how the great information content in well collected multivariate data can be expressed in terms of simple but illuminating plots, facilitating the understanding and interpretation of the data. The projection approach applies to a variety of data-analytical objectives, i.e., (i) summarizing and visualizing a data set, (ii) multivariate classification and discriminant analysis, and (iii) finding quantitative relationships among the variables. This works with any shape of data table, with many or few variables (columns), many or few observations (rows), and complete or incomplete data tables (missing data). In particular, projections handle data matrices with more variables than observations very well, and the data can be noisy and highly collinear. Authors: The five authors are all connected to the Umetrics company (www.umetrics.com) which has developed and sold software for multivariate analysis since 1987, as well as supports customers with training and consultations. Umetrics' customers include most large and medium sized companies in the pharmaceutical, biopharm, chemical, and semiconductor sectors.
Statistical Analysis With Missing Data
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Author : Roderick J. A. Little
language : en
Publisher: John Wiley & Sons
Release Date : 2014-08-25
Statistical Analysis With Missing Data written by Roderick J. A. Little and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-25 with Mathematics categories.
* Emphasizes the latest trends in the field. * Includes a new chapter on evolving methods. * Provides updated or revised material in most of the chapters.
Multivariate Data Analysis
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Author : Joseph F Hair (Jr)
language : en
Publisher:
Release Date : 2003
Multivariate Data Analysis written by Joseph F Hair (Jr) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Multivariate analysis categories.
Multivariate Data Analysis
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Author : William W. Cooley
language : en
Publisher:
Release Date : 1975
Multivariate Data Analysis written by William W. Cooley and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1975 with categories.
Analyzing Multivariate Data
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Author : Paul E. Green
language : en
Publisher:
Release Date : 1978
Analyzing Multivariate Data written by Paul E. Green and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1978 with Mathematics categories.
Single criterion, multiple predictor association; Multiple criterion, multiple predictor association; The analysis of interdependence.
Applied Multivariate Data Analysis
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Author : J. D. Jobson
language : en
Publisher:
Release Date : 1999
Applied Multivariate Data Analysis written by J. D. Jobson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with categories.