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Principles and practice of structural equation modeling
- Author / Creator
- Available as
- Physical
- Summary
-
Emphasizing concepts and rationale over mathematical minutiae, this is the most widely used, complete, and accessible structural equation modeling (SEM) text. Continuing the tradition of using real...
Emphasizing concepts and rationale over mathematical minutiae, this is the most widely used, complete, and accessible structural equation modeling (SEM) text. Continuing the tradition of using real data examples from a variety of disciplines, the significantly revised fourth edition incorporates recent developments such as Pearl's graphing theory and the structural causal model (SCM), measurement invariance, and more. Readers gain a comprehensive understanding of all phases of SEM, from data collection and screening to the interpretation and reporting of the results. Learning is enhanced by exercises with answers, rules to remember, and topic boxes. -- from back cover.
Details
- Creator
- Rex B. Kline
- Format
- Books
- Language
- English
- Publication
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- Fourth edition
- New York : The Guilford Press, [2015]
- ©2016
- Physical Details
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- xvii, 534 pages : illustrations ; 26 cm
- ISBNs
- 146252334X, 9781462523344, 9781462523351, 1462523358
- OCLC
- ocn907272101
- Includes bibliographical references (pages 489-509) and indexes.
- Part I. Concepts and tools -- Coming of age -- Regression fundamentals -- Significance testing and bootstrapping -- Data preparation and psychometrics review -- Computer tools -- Part II. Specification and identification -- Specification of observed variable (path) models -- Identification of observed-variable (path) models -- Graph theory and the structural causal model -- Specification and identification of confirmatory factor analysis models -- Specification and identification of structural regression models -- Part III. Analysis -- Estimation and local fit testing -- Global fit testing -- Analysis of confirmatory factor analysis models -- Analysis of structural regression models -- Part IV. Advanced techniques and best practices -- Mean structures and latent growth models -- Multiple-samples analysis and measurement invariance -- Interaction effects and multilevel structural equation modeling -- Best practices in structural equation modeling