1.

Record Nr.

UNINA9910131296503321

Autore

Cheung Mike W. L.

Titolo

Meta-analysis : a structural equation modeling approach / / Mike W. L. Cheung

Pubbl/distr/stampa

Chichester, England ; ; West Sussex, England : , : Wiley, , 2015

©2015

ISBN

1-118-95782-2

1-118-95783-0

Edizione

[1st edition]

Descrizione fisica

1 online resource (403 p.)

Disciplina

001.4/22

Soggetti

Statistics

Meta-analysis

Research - Statistical methods

Sampling (Statistics)

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references at the end of each chapters and index.

Nota di contenuto

""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                              ""

Sommario/riassunto

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