Analysis of Incomplete Multivariate Data

Analysis of Incomplete Multivariate Data
Author: J.L. Schafer
Publsiher: CRC Press
Total Pages: 448
Release: 1997-08-01
Genre: Mathematics
ISBN: 1439821860

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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.

Analysis of Incomplete Multivariate Data

Analysis of Incomplete Multivariate Data
Author: J. L. Schafer
Publsiher: Unknown
Total Pages: 429
Release: 1997
Genre: Electronic Book
ISBN: OCLC:778016646

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Analysis of Incomplete Multivariate Data

Analysis of Incomplete Multivariate Data
Author: J.L. Schafer
Publsiher: Chapman and Hall/CRC
Total Pages: 444
Release: 1997-08-01
Genre: Mathematics
ISBN: 0412040611

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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

Applied Missing Data Analysis
Author: Craig K. Enders
Publsiher: Guilford Press
Total Pages: 377
Release: 2010-04-23
Genre: Psychology
ISBN: 9781606236390

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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.

Analysis and Simulation of Incomplete Multivariate Data

Analysis and Simulation of Incomplete Multivariate Data
Author: J. L. Schafer
Publsiher: Unknown
Total Pages: 135
Release: 1996
Genre: Electronic Book
ISBN: OCLC:258570411

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Comprehensive Chemometrics

Comprehensive Chemometrics
Author: Steven Brown,Roma Tauler,Beata Walczak
Publsiher: Elsevier
Total Pages: 2944
Release: 2020-05-26
Genre: Science
ISBN: 9780444641663

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Comprehensive Chemometrics, Second Edition features expanded and updated coverage, along with new content that covers advances in the field since the previous edition published in 2009. Subject of note include updates in the fields of multidimensional and megavariate data analysis, omics data analysis, big chemical and biochemical data analysis, data fusion and sparse methods. The book follows a similar structure to the previous edition, using the same section titles to frame articles. Many chapters from the previous edition are updated, but there are also many new chapters on the latest developments. Presents integrated reviews of each chemical and biological method, examining their merits and limitations through practical examples and extensive visuals Bridges a gap in knowledge, covering developments in the field since the first edition published in 2009 Meticulously organized, with articles split into 4 sections and 12 sub-sections on key topics to allow students, researchers and professionals to find relevant information quickly and easily Written by academics and practitioners from various fields and regions to ensure that the knowledge within is easily understood and applicable to a large audience Presents integrated reviews of each chemical and biological method, examining their merits and limitations through practical examples and extensive visuals Bridges a gap in knowledge, covering developments in the field since the first edition published in 2009 Meticulously organized, with articles split into 4 sections and 12 sub-sections on key topics to allow students, researchers and professionals to find relevant information quickly and easily Written by academics and practitioners from various fields and regions to ensure that the knowledge within is easily understood and applicable to a large audience

Alternative Methods of Variable Selection in Linear Regression Models for Incomplete Multivariate Normal Data

Alternative Methods of Variable Selection in Linear Regression Models for Incomplete Multivariate Normal Data
Author: Xiaowei Yang
Publsiher: Unknown
Total Pages: 462
Release: 2002
Genre: Electronic Book
ISBN: UCLA:L0084183219

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Innovative Statistical Methods for Public Health Data

Innovative Statistical Methods for Public Health Data
Author: Ding-Geng (Din) Chen,Jeffrey Wilson
Publsiher: Springer
Total Pages: 351
Release: 2015-08-31
Genre: Medical
ISBN: 9783319185361

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The book brings together experts working in public health and multi-disciplinary areas to present recent issues in statistical methodological development and their applications. This timely book will impact model development and data analyses of public health research across a wide spectrum of analysis. Data and software used in the studies are available for the reader to replicate the models and outcomes. The fifteen chapters range in focus from techniques for dealing with missing data with Bayesian estimation, health surveillance and population definition and implications in applied latent class analysis, to multiple comparison and meta-analysis in public health data. Researchers in biomedical and public health research will find this book to be a useful reference and it can be used in graduate level classes.

Hierarchical Linear Models

Hierarchical Linear Models
Author: Stephen W. Raudenbush,Anthony S. Bryk
Publsiher: SAGE
Total Pages: 485
Release: 2002
Genre: Mathematics
ISBN: 076191904X

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Popular in its first edition for its rich, illustrative examples and lucid explanations of the theory and use of hierarchical linear models (HLM), the book has been updated to include: an intuitive introductory summary of the basic procedures for estimation and inference used with HLM models that only requires a minimal level of mathematical sophistication; a new section on multivariate growth models; a discussion of research synthesis or meta-analysis applications; aata analytic advice on centering of level-1 predictors, and new material on plausible value intervals and robust standard estimators.

Longitudinal Data Analysis

Longitudinal Data Analysis
Author: Garrett Fitzmaurice,Marie Davidian,Geert Verbeke,Geert Molenberghs
Publsiher: CRC Press
Total Pages: 632
Release: 2008-08-11
Genre: Mathematics
ISBN: 142001157X

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Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory and applications. It also focuses on the assorted challenges that arise in analyzing longitudinal data. After discussing historical aspects, leading researchers explore four broad themes: parametric modeling, nonparametric and semiparametric methods, joint models, and incomplete data. Each of these sections begins with an introductory chapter that provides useful background material and a broad outline to set the stage for subsequent chapters. Rather than focus on a narrowly defined topic, chapters integrate important research discussions from the statistical literature. They seamlessly blend theory with applications and include examples and case studies from various disciplines. Destined to become a landmark publication in the field, this carefully edited collection emphasizes statistical models and methods likely to endure in the future. Whether involved in the development of statistical methodology or the analysis of longitudinal data, readers will gain new perspectives on the field.

Applied Survey Data Analysis

Applied Survey Data Analysis
Author: Steven G. Heeringa,Brady T. West,Patricia A. Berglund
Publsiher: CRC Press
Total Pages: 568
Release: 2017-07-12
Genre: Mathematics
ISBN: 9781498761611

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Highly recommended by the Journal of Official Statistics, The American Statistician, and other journals, Applied Survey Data Analysis, Second Edition provides an up-to-date overview of state-of-the-art approaches to the analysis of complex sample survey data. Building on the wealth of material on practical approaches to descriptive analysis and regression modeling from the first edition, this second edition expands the topics covered and presents more step-by-step examples of modern approaches to the analysis of survey data using the newest statistical software. Designed for readers working in a wide array of disciplines who use survey data in their work, this book continues to provide a useful framework for integrating more in-depth studies of the theory and methods of survey data analysis. An example-driven guide to the applied statistical analysis and interpretation of survey data, the second edition contains many new examples and practical exercises based on recent versions of real-world survey data sets. Although the authors continue to use Stata for most examples in the text, they also continue to offer SAS, SPSS, SUDAAN, R, WesVar, IVEware, and Mplus software code for replicating the examples on the book’s updated website.

The Oxford Handbook of Panel Data

The Oxford Handbook of Panel Data
Author: Badi Hani Baltagi
Publsiher: Oxford Handbooks
Total Pages: 683
Release: 2015
Genre: Business & Economics
ISBN: 9780199940042

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Panel data econometrics has evolved rapidly over the past three decades. The field is of both theoretical and practical importance, and methods to deal with micro- and macroeconomic panel data are in high demand from practitioners. Applications in finance, development, trade, marketing, health, labor, and consumer economics attest to the usefulness of these methods in applied economics. THis book is a comprehensive source on panel data. It contains 20 chapters edited by Professor Badi Baltagi--one of the leading econometricians in the area of panel data econometrics--and authored by renowned experts in the field. The chapters are divided into two sections. Part I examines new developments in theory. It includes panel cointegration, dynamic panel data models, incidental parameters and dynamic panel modeling, and panel data models for discrete choice. The chapters in Part II target applications of panel data, including health, labor, marketing, trade, productivity and macro applications in panels.

Handbook of Psychology Research Methods in Psychology

Handbook of Psychology  Research Methods in Psychology
Author: Donald K. Freedheim,Irving B. Weiner,John A. Schinka,Wayne F. Velicer
Publsiher: John Wiley & Sons
Total Pages: 711
Release: 2003
Genre: Psychology
ISBN: 0471385131

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Includes established theories and cutting-edge developments. Presents the work of an international group of experts. Presents the nature, origin, implications, an future course of major unresolved issues in the area.

The Handbook of Marketing Research

The Handbook of Marketing Research
Author: Rajiv Grover,Marco Vriens
Publsiher: SAGE Publications
Total Pages: 720
Release: 2006-06-23
Genre: Business & Economics
ISBN: 9781506319452

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The Handbook of Marketing Research: Uses, Misuses, and Future Advances comprehensively explores the approaches for delivering market insights for fact-based decision making in a market-oriented firm. Divided into four parts, the Handbook addresses (1) the different nuances of delivering insights; (2) quantitative, qualitative, and online data gathering techniques; (3) basic and advanced data analysis methods; and (4) the substantial marketing issues that clients are interested in resolving through marketing research.

The Prevention and Treatment of Missing Data in Clinical Trials

The Prevention and Treatment of Missing Data in Clinical Trials
Author: National Research Council,Division of Behavioral and Social Sciences and Education,Committee on National Statistics,Panel on Handling Missing Data in Clinical Trials
Publsiher: National Academies Press
Total Pages: 162
Release: 2011-01-21
Genre: Medical
ISBN: 9780309158145

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Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participants discontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The Prevention and Treatment of Missing Data in Clinical Trials concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (1) careful design and conduct to limit the amount and impact of missing data and (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data.