Applied Meta Analysis For Social Science Research eBook Download PDF

Download Applied Meta Analysis For Social Science Research full books in PDF, epub, and Kindle. Read online Applied Meta Analysis For Social Science Research ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Applied Meta-Analysis for Social Science Research

Author: Noel A. Card

Publisher: Guilford Publications

Published: 2015-10-06

Total Pages: 401

ISBN-13: 1462525008

DOWNLOAD EBOOK

Offering pragmatic guidance for planning and conducting a meta-analytic review, this book is written in an engaging, nontechnical style that makes it ideal for graduate course use or self-study. The author shows how to identify questions that can be answered using meta-analysis, retrieve both published and unpublished studies, create a coding manual, use traditional and unique effect size indices, and write a meta-analytic review. An ongoing example illustrates meta-analytic techniques. In addition to the fundamentals, the book discusses more advanced topics, such as artifact correction, random- and mixed-effects models, structural equation representations, and multivariate procedures. User-friendly features include annotated equations; discussions of alternative approaches; and "Practical Matters" sections that give advice on topics not often discussed in other books, such as linking meta-analytic results with theory and the utility of meta-analysis software programs. ÿ

Book Synopsis Applied Meta-Analysis for Social Science Research by : Noel A. Card

Download or read book Applied Meta-Analysis for Social Science Research written by Noel A. Card and published by Guilford Publications. This book was released on 2015-10-06 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering pragmatic guidance for planning and conducting a meta-analytic review, this book is written in an engaging, nontechnical style that makes it ideal for graduate course use or self-study. The author shows how to identify questions that can be answered using meta-analysis, retrieve both published and unpublished studies, create a coding manual, use traditional and unique effect size indices, and write a meta-analytic review. An ongoing example illustrates meta-analytic techniques. In addition to the fundamentals, the book discusses more advanced topics, such as artifact correction, random- and mixed-effects models, structural equation representations, and multivariate procedures. User-friendly features include annotated equations; discussions of alternative approaches; and "Practical Matters" sections that give advice on topics not often discussed in other books, such as linking meta-analytic results with theory and the utility of meta-analysis software programs. ÿ

Methods of Meta-Analysis

Author: John E Hunter

Publisher: SAGE

Published: 2004-04-07

Total Pages: 620

ISBN-13: 9781412904797

DOWNLOAD EBOOK

Covering the most important developments in meta-analysis from 1990 to 2004, this text presents new patterns in research findings as well as updated information on existing topics.

Book Synopsis Methods of Meta-Analysis by : John E Hunter

Download or read book Methods of Meta-Analysis written by John E Hunter and published by SAGE. This book was released on 2004-04-07 with total page 620 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covering the most important developments in meta-analysis from 1990 to 2004, this text presents new patterns in research findings as well as updated information on existing topics.

Applied Meta-Analysis with R

Author: Ding-Geng (Din) Chen

Publisher: CRC Press

Published: 2013-05-03

Total Pages: 338

ISBN-13: 1466505990

DOWNLOAD EBOOK

In biostatistical research and courses, practitioners and students often lack a thorough understanding of how to apply statistical methods to synthesize biomedical and clinical trial data. Filling this knowledge gap, Applied Meta-Analysis with R shows how to implement statistical meta-analysis methods to real data using R. Drawing on their extensive research and teaching experiences, the authors provide detailed, step-by-step explanations of the implementation of meta-analysis methods using R. Each chapter gives examples of real studies compiled from the literature. After presenting the data and necessary background for understanding the applications, various methods for analyzing meta-data are introduced. The authors then develop analysis code using the appropriate R packages and functions. This systematic approach helps readers thoroughly understand the analysis methods and R implementation, enabling them to use R and the methods to analyze their own meta-data. Suitable as a graduate-level text for a meta-data analysis course, the book is also a valuable reference for practitioners and biostatisticians (even those with little or no experience in using R) in public health, medical research, governmental agencies, and the pharmaceutical industry.

Book Synopsis Applied Meta-Analysis with R by : Ding-Geng (Din) Chen

Download or read book Applied Meta-Analysis with R written by Ding-Geng (Din) Chen and published by CRC Press. This book was released on 2013-05-03 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: In biostatistical research and courses, practitioners and students often lack a thorough understanding of how to apply statistical methods to synthesize biomedical and clinical trial data. Filling this knowledge gap, Applied Meta-Analysis with R shows how to implement statistical meta-analysis methods to real data using R. Drawing on their extensive research and teaching experiences, the authors provide detailed, step-by-step explanations of the implementation of meta-analysis methods using R. Each chapter gives examples of real studies compiled from the literature. After presenting the data and necessary background for understanding the applications, various methods for analyzing meta-data are introduced. The authors then develop analysis code using the appropriate R packages and functions. This systematic approach helps readers thoroughly understand the analysis methods and R implementation, enabling them to use R and the methods to analyze their own meta-data. Suitable as a graduate-level text for a meta-data analysis course, the book is also a valuable reference for practitioners and biostatisticians (even those with little or no experience in using R) in public health, medical research, governmental agencies, and the pharmaceutical industry.

Practical Meta-Analysis

Author: Mark W. Lipsey

Publisher: SAGE Publications, Incorporated

Published: 2001

Total Pages: 270

ISBN-13:

DOWNLOAD EBOOK

"This book offers readers the best of both worlds: technical sophistication coupled with user-friendly, practical information for doing meta-analysis." -- Page 4 of cover.

Book Synopsis Practical Meta-Analysis by : Mark W. Lipsey

Download or read book Practical Meta-Analysis written by Mark W. Lipsey and published by SAGE Publications, Incorporated. This book was released on 2001 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book offers readers the best of both worlds: technical sophistication coupled with user-friendly, practical information for doing meta-analysis." -- Page 4 of cover.

Meta-Analysis

Author: Mike W.-L. Cheung

Publisher: John Wiley & Sons

Published: 2015-05-06

Total Pages: 401

ISBN-13: 1119993431

DOWNLOAD EBOOK

Presents a novel approach to conducting meta-analysis using structural equation modeling. Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment. Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the importance of SEM and meta-analysis in answering research questions. Key ideas in meta-analysis and SEM are briefly reviewed, and various meta-analytic models are then introduced and linked to the SEM framework. Fixed-, random-, and mixed-effects models in univariate and multivariate meta-analyses, three-level meta-analysis, and meta-analytic structural equation modeling, are introduced. Advanced topics, such as using restricted maximum likelihood estimation method and handling missing covariates, are also covered. Readers will learn a single framework to apply both meta-analysis and SEM. Examples in R and in Mplus are included. This book will be a valuable resource for statistical and academic researchers and graduate students carrying out meta-analyses, and will also be useful to researchers and statisticians using SEM in biostatistics. Basic knowledge of either SEM or meta-analysis will be helpful in understanding the materials in this book.

Book Synopsis Meta-Analysis by : Mike W.-L. Cheung

Download or read book Meta-Analysis written by Mike W.-L. Cheung and published by John Wiley & Sons. This book was released on 2015-05-06 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents a novel approach to conducting meta-analysis using structural equation modeling. Structural equation modeling (SEM) and meta-analysis are two powerful statistical methods in the educational, social, behavioral, and medical sciences. They are often treated as two unrelated topics in the literature. This book presents a unified framework on analyzing meta-analytic data within the SEM framework, and illustrates how to conduct meta-analysis using the metaSEM package in the R statistical environment. Meta-Analysis: A Structural Equation Modeling Approach begins by introducing the importance of SEM and meta-analysis in answering research questions. Key ideas in meta-analysis and SEM are briefly reviewed, and various meta-analytic models are then introduced and linked to the SEM framework. Fixed-, random-, and mixed-effects models in univariate and multivariate meta-analyses, three-level meta-analysis, and meta-analytic structural equation modeling, are introduced. Advanced topics, such as using restricted maximum likelihood estimation method and handling missing covariates, are also covered. Readers will learn a single framework to apply both meta-analysis and SEM. Examples in R and in Mplus are included. This book will be a valuable resource for statistical and academic researchers and graduate students carrying out meta-analyses, and will also be useful to researchers and statisticians using SEM in biostatistics. Basic knowledge of either SEM or meta-analysis will be helpful in understanding the materials in this book.

Handbook of Sustainability and Social Science Research

Author: Walter Leal Filho

Publisher: Springer

Published: 2017-10-26

Total Pages: 485

ISBN-13: 3319671227

DOWNLOAD EBOOK

In this handbook social science researchers who focus on sustainability present and discuss their findings, including empirical work, case studies, teaching and learning innovations, and applied projects. As such, the book offers a basis for the dissemination of information, ideas and experiences acquired in the execution of research projects, especially initiatives which have influenced behavior, decision-making, or policy. Furthermore, it introduces methodological approaches and projects which aim to offer a better understanding of sustainability across society and economic sectors. This multidisciplinary overview presents the work of researchers from across the spectrum of the social sciences. It stimulates innovative thinking on how social sciences influence sustainable development and vice-versa.

Book Synopsis Handbook of Sustainability and Social Science Research by : Walter Leal Filho

Download or read book Handbook of Sustainability and Social Science Research written by Walter Leal Filho and published by Springer. This book was released on 2017-10-26 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this handbook social science researchers who focus on sustainability present and discuss their findings, including empirical work, case studies, teaching and learning innovations, and applied projects. As such, the book offers a basis for the dissemination of information, ideas and experiences acquired in the execution of research projects, especially initiatives which have influenced behavior, decision-making, or policy. Furthermore, it introduces methodological approaches and projects which aim to offer a better understanding of sustainability across society and economic sectors. This multidisciplinary overview presents the work of researchers from across the spectrum of the social sciences. It stimulates innovative thinking on how social sciences influence sustainable development and vice-versa.

Applied Meta-Analysis with R and Stata

Author: Ding-Geng (Din) Chen

Publisher: CRC Press

Published: 2021-03-30

Total Pages: 457

ISBN-13: 0429592175

DOWNLOAD EBOOK

Review of the First Edition: The authors strive to reduce theory to a minimum, which makes it a self-learning text that is comprehensible for biologists, physicians, etc. who lack an advanced mathematics background. Unlike in many other textbooks, R is not introduced with meaningless toy examples; instead the reader is taken by the hand and shown around some analyses, graphics, and simulations directly relating to meta-analysis... A useful hands-on guide for practitioners who want to familiarize themselves with the fundamentals of meta-analysis and get started without having to plough through theorems and proofs. —Journal of Applied Statistics Statistical Meta-Analysis with R and Stata, Second Edition provides a thorough presentation of statistical meta-analyses (MA) with step-by-step implementations using R/Stata. The authors develop analysis step by step using appropriate R/Stata functions, which enables readers to gain an understanding of meta-analysis methods and R/Stata implementation so that they can use these two popular software packages to analyze their own meta-data. Each chapter gives examples of real studies compiled from the literature. After presenting the data and necessary background for understanding the applications, various methods for analyzing meta-data are introduced. The authors then develop analysis code using the appropriate R/Stata packages and functions. What’s New in the Second Edition: Adds Stata programs along with the R programs for meta-analysis Updates all the statistical meta-analyses with R/Stata programs Covers fixed-effects and random-effects MA, meta-regression, MA with rare-event, and MA-IPD vs MA-SS Adds five new chapters on multivariate MA, publication bias, missing data in MA, MA in evaluating diagnostic accuracy, and network MA Suitable as a graduate-level text for a meta-data analysis course, the book is also a valuable reference for practitioners and biostatisticians (even those with little or no experience in using R or Stata) in public health, medical research, governmental agencies, and the pharmaceutical industry.

Book Synopsis Applied Meta-Analysis with R and Stata by : Ding-Geng (Din) Chen

Download or read book Applied Meta-Analysis with R and Stata written by Ding-Geng (Din) Chen and published by CRC Press. This book was released on 2021-03-30 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: Review of the First Edition: The authors strive to reduce theory to a minimum, which makes it a self-learning text that is comprehensible for biologists, physicians, etc. who lack an advanced mathematics background. Unlike in many other textbooks, R is not introduced with meaningless toy examples; instead the reader is taken by the hand and shown around some analyses, graphics, and simulations directly relating to meta-analysis... A useful hands-on guide for practitioners who want to familiarize themselves with the fundamentals of meta-analysis and get started without having to plough through theorems and proofs. —Journal of Applied Statistics Statistical Meta-Analysis with R and Stata, Second Edition provides a thorough presentation of statistical meta-analyses (MA) with step-by-step implementations using R/Stata. The authors develop analysis step by step using appropriate R/Stata functions, which enables readers to gain an understanding of meta-analysis methods and R/Stata implementation so that they can use these two popular software packages to analyze their own meta-data. Each chapter gives examples of real studies compiled from the literature. After presenting the data and necessary background for understanding the applications, various methods for analyzing meta-data are introduced. The authors then develop analysis code using the appropriate R/Stata packages and functions. What’s New in the Second Edition: Adds Stata programs along with the R programs for meta-analysis Updates all the statistical meta-analyses with R/Stata programs Covers fixed-effects and random-effects MA, meta-regression, MA with rare-event, and MA-IPD vs MA-SS Adds five new chapters on multivariate MA, publication bias, missing data in MA, MA in evaluating diagnostic accuracy, and network MA Suitable as a graduate-level text for a meta-data analysis course, the book is also a valuable reference for practitioners and biostatisticians (even those with little or no experience in using R or Stata) in public health, medical research, governmental agencies, and the pharmaceutical industry.