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Record Nr. |
UNINA9910131296503321 |
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Autore |
Cheung Mike W. L. |
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Titolo |
Meta-analysis : a structural equation modeling approach / / Mike W. L. Cheung |
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Pubbl/distr/stampa |
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Chichester, England ; ; West Sussex, England : , : Wiley, , 2015 |
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©2015 |
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ISBN |
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1-118-95782-2 |
1-118-95783-0 |
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Edizione |
[1st edition] |
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Descrizione fisica |
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1 online resource (403 p.) |
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Disciplina |
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Soggetti |
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Statistics |
Meta-analysis |
Research - Statistical methods |
Sampling (Statistics) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters and index. |
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Nota di contenuto |
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""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 |
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""; ""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 "" |
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Sommario/riassunto |
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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 impo |
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