Principles and Practice of Structural Equation Modeling

Autor: 
Język: 
english
Oprawa: 
Twarda
Liczba stron: 
494
Significantly revised, the fifth edition of the most complete, accessible text now covers all three approaches to structural equation modeling (SEM)--covariance-based SEM, nonparametric SEM (Pearl's s ...Cały opis
514,60 zł

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ISBN9781462552009
AutorKline Rex B.
WydawcaGuilford Pubn
Językenglish
OprawaPevná vazba
Rok wydania2023
Liczba stron494

Opis książki

Significantly revised, the fifth edition of the most complete, accessible text now covers all three approaches to structural equation modeling (SEM)--covariance-based SEM, nonparametric SEM (Pearl's structural causal model), and composite SEM (partial least squares path modeling). With increased emphasis on freely available software tools such as the R lavaan package, the text uses data examples from multiple disciplines to provide a comprehensive understanding of all phases of SEM--what to know, best practices, and pitfalls to avoid. It includes exercises with answers, rules to remember, topic boxes, and new self-tests on significance testing, regression, and psychometrics. The companion website supplies helpful primers on these topics as well as data, syntax, and output for the book's examples, in files that can be opened with any basic text editor.

New to This Edition
*Chapters on composite SEM, also called partial least squares path modeling or variance-based SEM
conducting SEM analyses in small samples
and recent developments in mediation analysis.
*Coverage of new reporting standards for SEM analyses
piecewise SEM, also called confirmatory path analysis
comparing alternative models fitted to the same data
and issues in multiple-group SEM.
*Extended tutorials on techniques for dealing with missing data in SEM and instrumental variable methods to deal with confounding of target causal effects.

Pedagogical Features
*New self-tests of knowledge about background topics (significance testing, regression, and psychometrics) with scoring key and online primers.
*End-of-chapter suggestions for further reading and exercises with answers.
*Troublesome examples from real data, with guidance for handling typical problems in analyses.
*Topic boxes on special issues and boxed rules to remember.
*Website promoting a learn-by-doing approach, including data, extensively annotated syntax, and output files for all the book's detailed examples.

 

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