Marginal Models In Analysis Of Correlated Binary Data With Time Dependent Covariates

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Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates

Jeffrey R. Wilson,Elsa Vazquez-Arreola,(Din) Ding-Geng Chen
Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates Book PDF

Author : Jeffrey R. Wilson,Elsa Vazquez-Arreola,(Din) Ding-Geng Chen
Publisher : Springer Nature
Page : 182 pages
File Size : 48,9 Mb
Release : 2020-09-28
Category : Medical
ISBN : 9783030489045

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Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates by Jeffrey R. Wilson,Elsa Vazquez-Arreola,(Din) Ding-Geng Chen Pdf

This monograph provides a concise point of research topics and reference for modeling correlated response data with time-dependent covariates, and longitudinal data for the analysis of population-averaged models, highlighting methods by a variety of pioneering scholars. While the models presented in the volume are applied to health and health-related data, they can be used to analyze any kind of data that contain covariates that change over time. The included data are analyzed with the use of both R and SAS, and the data and computing programs are provided to readers so that they can replicate and implement covered methods. It is an excellent resource for scholars of both computational and methodological statistics and biostatistics, particularly in the applied areas of health. ​

Innovative Statistical Methods for Public Health Data

Ding-Geng (Din) Chen,Jeffrey Wilson
Innovative Statistical Methods for Public Health Data Book PDF

Author : Ding-Geng (Din) Chen,Jeffrey Wilson
Publisher : Springer
Page : 351 pages
File Size : 52,6 Mb
Release : 2015-08-31
Category : Medical
ISBN : 9783319185361

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Innovative Statistical Methods for Public Health Data by Ding-Geng (Din) Chen,Jeffrey Wilson Pdf

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.

Modeling Binary Correlated Responses using SAS, SPSS and R

Jeffrey R. Wilson,Kent A. Lorenz
Modeling Binary Correlated Responses using SAS SPSS and R Book PDF

Author : Jeffrey R. Wilson,Kent A. Lorenz
Publisher : Springer
Page : 264 pages
File Size : 53,6 Mb
Release : 2015-10-12
Category : Mathematics
ISBN : 9783319238050

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Modeling Binary Correlated Responses using SAS, SPSS and R by Jeffrey R. Wilson,Kent A. Lorenz Pdf

Statistical tools to analyze correlated binary data are spread out in the existing literature. This book makes these tools accessible to practitioners in a single volume. Chapters cover recently developed statistical tools and statistical packages that are tailored to analyzing correlated binary data. The authors showcase both traditional and new methods for application to health-related research. Data and computer programs will be publicly available in order for readers to replicate model development, but learning a new statistical language is not necessary with this book. The inclusion of code for R, SAS, and SPSS allows for easy implementation by readers. For readers interested in learning more about the languages, though, there are short tutorials in the appendix. Accompanying data sets are available for download through the book s website. Data analysis presented in each chapter will provide step-by-step instructions so these new methods can be readily applied to projects. Researchers and graduate students in Statistics, Epidemiology, and Public Health will find this book particularly useful.

Statistical Regression Modeling with R

Ding-Geng (Din) Chen,Jenny K. Chen
Statistical Regression Modeling with R Book PDF

Author : Ding-Geng (Din) Chen,Jenny K. Chen
Publisher : Springer Nature
Page : 239 pages
File Size : 47,7 Mb
Release : 2021-04-08
Category : Mathematics
ISBN : 9783030675837

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Statistical Regression Modeling with R by Ding-Geng (Din) Chen,Jenny K. Chen Pdf

This book provides a concise point of reference for the most commonly used regression methods. It begins with linear and nonlinear regression for normally distributed data, logistic regression for binomially distributed data, and Poisson regression and negative-binomial regression for count data. It then progresses to these regression models that work with longitudinal and multi-level data structures. The volume is designed to guide the transition from classical to more advanced regression modeling, as well as to contribute to the rapid development of statistics and data science. With data and computing programs available to facilitate readers' learning experience, Statistical Regression Modeling promotes the applications of R in linear, nonlinear, longitudinal and multi-level regression. All included datasets, as well as the associated R program in packages nlme and lme4 for multi-level regression, are detailed in Appendix A. This book will be valuable in graduate courses on applied regression, as well as for practitioners and researchers in the fields of data science, statistical analytics, public health, and related fields.

Progress in Applied Mathematical Modeling

Fengshan Yang
Progress in Applied Mathematical Modeling Book PDF

Author : Fengshan Yang
Publisher : Nova Publishers
Page : 386 pages
File Size : 47,8 Mb
Release : 2008
Category : Mathematics
ISBN : 1600219764

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Progress in Applied Mathematical Modeling by Fengshan Yang Pdf

This book presents new research related to the mathematical modelling of engineering and environmental processes, manufacturing, and industrial systems. It includes heat transfer, fluid mechanics, CFD, and transport phenomena; solid mechanics and mechanics of metals; electromagnets and MHD; reliability modelling and system optimisation; finite volume, finite element, and boundary element procedures; decision sciences in an industrial and manufacturing context; civil engineering systems and structures; mineral and energy resources; relevant software engineering issues associated with CAD and CAE; and materials and metallurgical engineering.

Mixed Effects Models for Complex Data

Lang Wu
Mixed Effects Models for Complex Data Book PDF

Author : Lang Wu
Publisher : CRC Press
Page : 431 pages
File Size : 44,5 Mb
Release : 2009-11-11
Category : Mathematics
ISBN : 1420074083

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Mixed Effects Models for Complex Data by Lang Wu Pdf

Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.

Advances and Challenges in Parametric and Semi-parametric Analysis for Correlated Data

Brajendra C. Sutradhar
Advances and Challenges in Parametric and Semi parametric Analysis for Correlated Data Book PDF

Author : Brajendra C. Sutradhar
Publisher : Springer
Page : 256 pages
File Size : 53,7 Mb
Release : 2016-06-15
Category : Mathematics
ISBN : 9783319312606

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Advances and Challenges in Parametric and Semi-parametric Analysis for Correlated Data by Brajendra C. Sutradhar Pdf

This proceedings volume contains eight selected papers that were presented in the International Symposium in Statistics (ISS) 2015 On Advances in Parametric and Semi-parametric Analysis of Multivariate, Time Series, Spatial-temporal, and Familial-longitudinal Data, held in St. John’s, Canada from July 6 to 8, 2015. The main objective of the ISS-2015 was the discussion on advances and challenges in parametric and semi-parametric analysis for correlated data in both continuous and discrete setups. Thus, as a reflection of the theme of the symposium, the eight papers of this proceedings volume are presented in four parts. Part I is comprised of papers examining Elliptical t Distribution Theory. In Part II, the papers cover spatial and temporal data analysis. Part III is focused on longitudinal multinomial models in parametric and semi-parametric setups. Finally Part IV concludes with a paper on the inferences for longitudinal data subject to a challenge of important covariates selection from a set of large number of covariates available for the individuals in the study.

Generalized Estimating Equations

Andreas Ziegler
Generalized Estimating Equations Book PDF

Author : Andreas Ziegler
Publisher : Springer Science & Business Media
Page : 155 pages
File Size : 44,6 Mb
Release : 2011-06-17
Category : Mathematics
ISBN : 9781461404996

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Generalized Estimating Equations by Andreas Ziegler Pdf

Generalized estimating equations have become increasingly popular in biometrical, econometrical, and psychometrical applications because they overcome the classical assumptions of statistics, i.e. independence and normality, which are too restrictive for many problems. Therefore, the main goal of this book is to give a systematic presentation of the original generalized estimating equations (GEE) and some of its further developments. Subsequently, the emphasis is put on the unification of various GEE approaches. This is done by the use of two different estimation techniques, the pseudo maximum likelihood (PML) method and the generalized method of moments (GMM). The author details the statistical foundation of the GEE approach using more general estimation techniques. The book could therefore be used as basis for a course to graduate students in statistics, biostatistics, or econometrics, and will be useful to practitioners in the same fields.

The SAGE Handbook of Multilevel Modeling

Marc A. Scott,Jeffrey S. Simonoff,Brian D. Marx
The SAGE Handbook of Multilevel Modeling Book PDF

Author : Marc A. Scott,Jeffrey S. Simonoff,Brian D. Marx
Publisher : SAGE
Page : 745 pages
File Size : 46,9 Mb
Release : 2013-08-31
Category : Social Science
ISBN : 9781473971318

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The SAGE Handbook of Multilevel Modeling by Marc A. Scott,Jeffrey S. Simonoff,Brian D. Marx Pdf

In this important new Handbook, the editors have gathered together a range of leading contributors to introduce the theory and practice of multilevel modeling. The Handbook establishes the connections in multilevel modeling, bringing together leading experts from around the world to provide a roadmap for applied researchers linking theory and practice, as well as a unique arsenal of state-of-the-art tools. It forges vital connections that cross traditional disciplinary divides and introduces best practice in the field. Part I establishes the framework for estimation and inference, including chapters dedicated to notation, model selection, fixed and random effects, and causal inference. Part II develops variations and extensions, such as nonlinear, semiparametric and latent class models. Part III includes discussion of missing data and robust methods, assessment of fit and software. Part IV consists of exemplary modeling and data analyses written by methodologists working in specific disciplines. Combining practical pieces with overviews of the field, this Handbook is essential reading for any student or researcher looking to apply multilevel techniques in their own research.

Computational and Methodological Statistics and Biostatistics

Andriëtte Bekker,(Din) Ding-Geng Chen,Johannes T. Ferreira
Computational and Methodological Statistics and Biostatistics Book PDF

Author : Andriëtte Bekker,(Din) Ding-Geng Chen,Johannes T. Ferreira
Publisher : Springer Nature
Page : 543 pages
File Size : 50,9 Mb
Release : 2020-08-10
Category : Medical
ISBN : 9783030421960

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Computational and Methodological Statistics and Biostatistics by Andriëtte Bekker,(Din) Ding-Geng Chen,Johannes T. Ferreira Pdf

In the statistical domain, certain topics have received considerable attention during the last decade or so, necessitated by the growth and evolution of data and theoretical challenges. This growth has invariably been accompanied by computational advancement, which has presented end users as well as researchers with the necessary opportunities to handle data and implement modelling solutions for statistical purposes. Showcasing the interplay among a variety of disciplines, this book offers pioneering theoretical and applied solutions to practice-oriented problems. As a carefully curated collection of prominent international thought leaders, it fosters collaboration between statisticians and biostatisticians and provides an array of thought processes and tools to its readers. The book thereby creates an understanding and appreciation of recent developments as well as an implementation of these contributions within the broader framework of both academia and industry. Computational and Methodological Statistics and Biostatistics is composed of three main themes: • Recent developments in theory and applications of statistical distributions;• Recent developments in supervised and unsupervised modelling;• Recent developments in biostatistics; and also features programming code and accompanying algorithms to enable readers to replicate and implement methodologies. Therefore, this monograph provides a concise point of reference for a variety of current trends and topics within the statistical domain. With interdisciplinary appeal, it will be useful to researchers, graduate students, and practitioners in statistics, biostatistics, clinical methodology, geology, data science, and actuarial science, amongst others.

Marginal Models

Wicher Bergsma,Marcel A. Croon,Jacques A. Hagenaars
Marginal Models Book PDF

Author : Wicher Bergsma,Marcel A. Croon,Jacques A. Hagenaars
Publisher : Springer Science & Business Media
Page : 274 pages
File Size : 54,9 Mb
Release : 2009-04-03
Category : Science
ISBN : 9780387096100

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Marginal Models by Wicher Bergsma,Marcel A. Croon,Jacques A. Hagenaars Pdf

Marginal Models for Dependent, Clustered, and Longitudinal Categorical Data provides a comprehensive overview of the basic principles of marginal modeling and offers a wide range of possible applications. Marginal models are often the best choice for answering important research questions when dependent observations are involved, as the many real world examples in this book show. In the social, behavioral, educational, economic, and biomedical sciences, data are often collected in ways that introduce dependencies in the observations to be compared. For example, the same respondents are interviewed at several occasions, several members of networks or groups are interviewed within the same survey, or, within families, both children and parents are investigated. Statistical methods that take the dependencies in the data into account must then be used, e.g., when observations at time one and time two are compared in longitudinal studies. At present, researchers almost automatically turn to multi-level models or to GEE estimation to deal with these dependencies. Despite the enormous potential and applicability of these recent developments, they require restrictive assumptions on the nature of the dependencies in the data. The marginal models of this book provide another way of dealing with these dependencies, without the need for such assumptions, and can be used to answer research questions directly at the intended marginal level. The maximum likelihood method, with its attractive statistical properties, is used for fitting the models. This book has mainly been written with applied researchers in mind. It includes many real world examples, explains the types of research questions for which marginal modeling is useful, and provides a detailed description of how to apply marginal models for a great diversity of research questions. All these examples are presented on the book's website (www.cmm.st), along with user friendly programs.

Correlated Data Analysis: Modeling, Analytics, and Applications

Peter X. -K. Song
Correlated Data Analysis Modeling Analytics and Applications Book PDF

Author : Peter X. -K. Song
Publisher : Springer Science & Business Media
Page : 352 pages
File Size : 47,8 Mb
Release : 2007-06-30
Category : Mathematics
ISBN : 9780387713939

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Correlated Data Analysis: Modeling, Analytics, and Applications by Peter X. -K. Song Pdf

This book covers recent developments in correlated data analysis. It utilizes the class of dispersion models as marginal components in the formulation of joint models for correlated data. This enables the book to cover a broader range of data types than the traditional generalized linear models. The reader is provided with a systematic treatment for the topic of estimating functions, and both generalized estimating equations (GEE) and quadratic inference functions (QIF) are studied as special cases. In addition to the discussions on marginal models and mixed-effects models, this book covers new topics on joint regression analysis based on Gaussian copulas.

Biostatistical Genetics and Genetic Epidemiology

Robert C. Elston,Jane M. Olson,Lyle Palmer
Biostatistical Genetics and Genetic Epidemiology Book PDF

Author : Robert C. Elston,Jane M. Olson,Lyle Palmer
Publisher : John Wiley & Sons
Page : 860 pages
File Size : 49,6 Mb
Release : 2002-04-22
Category : Medical
ISBN : 0471486310

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Biostatistical Genetics and Genetic Epidemiology by Robert C. Elston,Jane M. Olson,Lyle Palmer Pdf

"Human Genetics and Genetic Epidemiology" ist der 3. Band aus der sehr erfolgreichen Reihe 'Wiley Biostatistics Reference Series', die auf Artikeln der "Encyclopedia of Biostatistics" basiert. Dieser Band gibt einen topaktuellen und umfassenden Überblick über ein Forschungsgebiet, das insbesondere im Zuge des Human-Genomprojekts eine regelrechte Explosion an Forschungsaktivitäten erlebt hat. Enthalten sind komplett aktualisierte Artikel aus der "Encyclopedia of Biostatistics" sowie über 25% neue Artikel. Mit einem komplexen System an Querverweisen, die das Auffinden der gewünschten Information erheblich erleichtern. Eine interessante Lektüre für Genetiker, Epidemiologen, Biostatistiker und Forscher in diesen Bereichen.

Issues in Healthcare Communication and Information Technology: 2011 Edition

Anonim
Issues in Healthcare Communication and Information Technology 2011 Edition Book PDF

Author : Anonim
Publisher : ScholarlyEditions
Page : 243 pages
File Size : 41,5 Mb
Release : 2012-01-09
Category : Medical
ISBN : 9781464967412

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Issues in Healthcare Communication and Information Technology: 2011 Edition by Anonim Pdf

Issues in Healthcare Communication and Information Technology: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Healthcare Communication and Information Technology. The editors have built Issues in Healthcare Communication and Information Technology: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Healthcare Communication and Information Technology in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Healthcare Communication and Information Technology: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

Statistical Methods for the Analysis of Repeated Measurements

Charles S. Davis
Statistical Methods for the Analysis of Repeated Measurements Book PDF

Author : Charles S. Davis
Publisher : Springer Science & Business Media
Page : 416 pages
File Size : 44,9 Mb
Release : 2008-01-10
Category : Mathematics
ISBN : 9780387215730

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Statistical Methods for the Analysis of Repeated Measurements by Charles S. Davis Pdf

A comprehensive introduction to a wide variety of statistical methods for the analysis of repeated measurements. It is designed to be both a useful reference for practitioners and a textbook for a graduate-level course focused on methods for the analysis of repeated measurements. The important features of this book include a comprehensive coverage of classical and recent methods for continuous and categorical outcome variables; numerous homework problems at the end of each chapter; and the extensive use of real data sets in examples and homework problems.