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Linear Causal Modeling with Structural Equations
Abstract
Emphasizing causation as a functional relationship between variables, this book provides comprehensive coverage on the basics of SEM. It takes readers through the process of identifying, estimating, analyzing, and evaluating a range of models. The author discusses the history and philosophy of causality and its place in science and presents graph theory as a tool for the design and analysis of causal models. He explains how the algorithms in SEM are derived and how they work, covers various indices and tests for evaluating the fit of structural equation models to data, and explores recent research in graph theory, path tracing rules, and model evaluation.
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Cited by
A general approach to causal mediation analysis.
Imai, K., Keele, L., & Tingley, D. (2010) · Psychological Methods · doi:10.1037/a0020761 · Cited by 4,143
Interpretation and identification of causal mediation
Pearl, J. (2014) · Psychological Methods · doi:10.1037/a0036434 · Cited by 554
Heene, M., Hilbert, S., Draxler, C., Ziegler, M., & Bühner, M. (2011) · Psychological Methods · doi:10.1037/a0024917 · Cited by 406
Ullman, J. B., & Bentler, P. M. (2012) · Handbook of Psychology, Second Edition · doi:10.1002/9781118133880.hop202023 · Cited by 330
Antonakis, J., Bendahan, S., Jacquart, P., & Lalive, R. (2014) · Oxford Handbooks Online · doi:10.1093/oxfordhb/9780199755615.013.007 · Cited by 305
Metadata
- Authors
- Mulaik, S. A.
- Venue
- Chapman & Hall/CRC eBooks
- Publisher
- Chapman and Hall/CRC
- Published
- 2009-06-16
- OpenAlex
- W633035399
- Cited by
- 278
- References
- 0
- FWCI
- 5.38
- Type
- book
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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