05568nam 2200757 450 991013129650332120220718132848.01-118-95782-21-118-95783-0(CKB)3710000000391757(EBL)1895808(OCoLC)904194680(SSID)ssj0001461986(PQKBManifestationID)12551069(PQKBTitleCode)TC0001461986(PQKBWorkID)11478792(PQKB)11040724(PQKBManifestationID)16051824(PQKB)23749949(DLC) 2015008108(Au-PeEL)EBL1895808(CaPaEBR)ebr11041411(CaONFJC)MIL770076(CaSebORM)9781119993438(MiAaPQ)EBC1895808(PPN)191912093(EXLCZ)99371000000039175720150416h20152015 uy 0engur|n|---|||||txtccrMeta-analysis a structural equation modeling approach /Mike W. L. Cheung1st editionChichester, England ;West Sussex, England :Wiley,2015.©20151 online resource (403 p.)Description based upon print version of record.1-118-95781-4 1-119-99343-1 Includes bibliographical references at the end of each chapters and index.""Cover ""; ""Title Page ""; ""Copyright ""; ""Contents ""; ""Preface ""; ""Acknowledgments ""; ""List of abbreviations ""; ""List of figures ""; ""List of tables ""; ""Chapter 1 Introduction ""; ""1.1 What is meta-analysis? ""; ""1.2 What is structural equation modeling? """"1.3 Reasons for writing a book on meta-analysis and structural equation modeling """"1.3.1 Benefits to users of structural equation modeling and meta-analysis ""; ""1.4 Outline of the following chapters ""; ""1.4.1 Computer examples and data sets used in this book """"1.5 Concluding remarks and further readings """"References ""; ""Chapter 2 Brief review of structural equation modeling ""; ""2.1 Introduction ""; ""2.2 Model specification ""; ""2.2.1 Equations ""; ""2.2.2 Path diagram ""; ""2.2.3 Matrix representation ""; ""2.3 Common structural equation models """"2.3.1 Path analysis """"2.3.2 Confirmatory factor analysis ""; ""2.3.3 Structural equation model ""; ""2.3.4 Latent growth model ""; ""2.3.5 Multiple-group analysis ""; ""2.4 Estimation methods, test statistics, and goodness-of-fit indices ""; ""2.4.1 Maximum likelihood estimation """"2.4.2 Weighted least squares """"2.4.3 Multiple-group analysis ""; ""2.4.4 Likelihood ratio test and Wald test ""; ""2.4.5 Confidence intervals on parameter estimates ""; ""2.4.6 Test statistics versus goodness-of-fit indices ""; ""2.5 Extensions on structural equation modeling """"2.5.1 Phantom variables ""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 impoStatisticsMeta-analysisResearchStatistical methodsSampling (Statistics)Statistics.Meta-analysis.ResearchStatistical methods.Sampling (Statistics)001.4/22Cheung Mike W. L.902637MiAaPQMiAaPQMiAaPQBOOK9910131296503321Meta-analysis2017812UNINA