Meta Analysis A Structural Equation Modeling Approach

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Meta-Analysis A Structural Equation Modeling Approach by Mike W. L. Cheung | PDF Free Download.


Guide Particulars :
Language English
Pages 403
Format PDF
Measurement 2.16 MB

Meta Analysis Contents


  • Introduction
  • Temporary evaluate of structural equation modeling
  • Computing impact sizes for meta-analysis
  • Univariate meta-analysis
  • Multivariate meta-analysis
  • Three-level meta-analysis
  • Meta-analytic structural equation modeling
  • Superior matters in SEM-based meta-analysis
  • Conducting meta-analysis with Mplus

Preface to Meta Analysis A Structural Equation Modeling Approach


Function of This Guide

There have been two functions for scripting this e book. One was private and the opposite was extra “formal.” I’ll give the non-public one first.

The first motivation for scripting this e book was to doc my very own journey in studying structural equation modeling (SEM) and meta-analysis.

The journey started once I was an undergraduate pupil. I first realized SEM from Wai Chan, my former supervisor.

After studying a bit from the giants in SEM, resembling Karl Jöreskog, Peter Bentler, Bengt Muthén, Kenneth Bollen, Michael Browne, Michael Neale, and Roderick McDonald, amongst others, I discovered SEM fascinating. It appears that evidently SEM is the statistical framework for all information evaluation.

Almost all of the statistical methods I realized could be formulated as structural equation fashions. In my graduate research, I got here throughout a special method—a meta-analysis. I realized meta-analysis by studying the traditional e book by Larry Hedges and Ingram Olkin.

I used to be impressed {that a} easy but elegant statistical mannequin may very well be used to synthesize findings throughout research.

It appears that evidently meta-analysis is the important thing to advance data by combining outcomes from totally different research. As I used to be skilled with the SEM background, all the pieces appears to be like like a structural equation mannequin to me.

I requested the query, “may a meta-analysis by a structural equation mannequin?” This e book summarized my journey to reply this query prior to now one and a half a long time.

Now, I’ll give a extra formal objective for this e book. With the advances in statistics and computing, researchers have extra statistical instruments to reply their analysis questions. SEM and meta-analysis are two highly effective statistical methods within the social, instructional, behavioral, and medical sciences.

SEM is a well-liked software to check hypothesized fashions by modeling the latent and noticed variables in main analysis, whereas meta-analysis is a de facto software to synthesize analysis findings from a pool of empirical research. These two methods are normally handled as two unrelated matters within the literature.

They’ve their very own strengths, weaknesses, assumptions, fashions, terminologies, software program packages, audiences, and even journals (Structural Equation Modeling: A Multidisciplinary Journal and Analysis Synthesis Strategies).

Researchers working in a single space hardly ever discuss with the work within the different space. Advances in a single space have mainly no affect on the opposite space. There have been two main targets for this e book.

The primary one was to current the current methodological advances on integrating meta-analysis and SEM—the SEM-based meta-analysis (utilizing SEM to conducting meta-analysis) and meta-analytic structural equation modeling (conducting a meta-analysis on correlation matrices for the aim of becoming structural equation fashions on the pooled correlation matrix).

It’s my hope {that a} unified framework will probably be made out there to researchers conducting each main information evaluation and meta-analysis.

A single framework can simply translate advances from one area to the opposite fields. Researchers don’t must reinvent the wheels once more. The second objective was to supply accessible computational instruments for researchers conducting meta-analyses.

The metaSEM package deal within the R statistical setting, which is accessible at http://courses.nus.edu.sg/course/psycwlm/Internet/metaSEM/, was developed to fill this hole. Utilizing the OpenMx package deal because the workhorse, the metaSEM package deal carried out a lot of the strategies mentioned on this e book.

Full examples in R code are supplied to information readers to suit varied meta-analytic fashions. Apart from the R code, Mplus was additionally used for instance a few of the examples on this e book. R (3.1.1), OpenMx (2.0.0-3654), metaSEM (0.9-0), meta for (1.9-3), lava (0.5-17.698), and Mplus (7.2) had been utilized in scripting this e book. The output format could also be barely totally different from the variations that you’re utilizing.

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Book Description:

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.

Meta-Analysis: A Structural Equation Modeling Approach

Author(s): Mike W.-L. Cheung

Publisher: Wiley, Year: 2015

ISBN: 1119993431,9781119993438


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