Name: Meta-Analysis: A Structural Equation Modeling Approach (en Inglés)
Price: 82240.00 CLP
Availability: InStock
Author: Cheung, Mike W. -L
ISBN: 9781119993438

portada Meta-Analysis: A Structural Equation Modeling Approach (en Inglés)

Formato

Libro Físico

Autor

Mike W. -L Cheung

Editorial

Wiley

Año

2015

Idioma

Inglés

N° páginas

400

Encuadernación

Tapa Dura

Dimensiones

22.9 x 15.5 x 2.3 cm

Peso

0.64 kg.

ISBN13

9781119993438

N° edición

Categorías

Probabilidad y estadística

Meta-Analysis: A Structural Equation Modeling Approach (en Inglés)

Mike W. -L Cheung (Autor) · Wiley · Tapa Dura

Libro Físico

$ 82.240

$ 137.060

Ahorras: $ 54.820

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Origen: Reino Unido (Costos de importación incluídos en el precio)

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Reseña del libro "Meta-Analysis: A Structural Equation Modeling Approach (en Inglés)"

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.