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Winner of the 2015 Sugiyama Meiko Award (Publication Award) of the
Behaviormetric Society of Japan Developed by the authors,
generalized structured component analysis is an alternative to two
longstanding approaches to structural equation modeling: covariance
structure analysis and partial least squares path modeling.
Generalized structured component analysis allows researchers to
evaluate the adequacy of a model as a whole, compare a model to
alternative specifications, and conduct complex analyses in a
straightforward manner. Generalized Structured Component Analysis:
A Component-Based Approach to Structural Equation Modeling provides
a detailed account of this novel statistical methodology and its
various extensions. The authors present the theoretical
underpinnings of generalized structured component analysis and
demonstrate how it can be applied to various empirical examples.
The book enables quantitative methodologists, applied researchers,
and practitioners to grasp the basic concepts behind this new
approach and apply it to their own research. The book emphasizes
conceptual discussions throughout while relegating more technical
intricacies to the chapter appendices. Most chapters compare
generalized structured component analysis to partial least squares
path modeling to show how the two component-based approaches differ
when addressing an identical issue. The authors also offer a free,
online software program (GeSCA) and an Excel-based software program
(XLSTAT) for implementing the basic features of generalized
structured component analysis.
The volume represents presentations given at the 86th annual
meeting of the Psychometric Society, held virtually on July
19–23, 2021. About 500 individuals contributed paper
presentations, symposiums, poster presentations, pre-conference
workshops, keynote presentations, and invited presentations. Since
the 77th meeting, Springer has published the conference proceedings
volume from this annual meeting to allow presenters to share their
work and ideas with the wider research community, while still
undergoing a thorough review process. This proceedings covers a
diverse set of psychometric topics, including item response theory,
Bayesian models, reliability, longitudinal measures, and cognitive
diagnostic models.
The volume represents presentations given at the 87th annual
meeting of the Psychometric Society, held in Bologna, Italy at July
11–15, 2022. The proceedings cover a diverse set of
psychometric topics, including item response theory, Bayesian
models, reliability, latent variable models, causal inference, and
cognitive diagnostic models.
Winner of the 2015 Sugiyama Meiko Award (Publication Award) of the
Behaviormetric Society of Japan Developed by the authors,
generalized structured component analysis is an alternative to two
longstanding approaches to structural equation modeling: covariance
structure analysis and partial least squares path modeling.
Generalized structured component analysis allows researchers to
evaluate the adequacy of a model as a whole, compare a model to
alternative specifications, and conduct complex analyses in a
straightforward manner. Generalized Structured Component Analysis:
A Component-Based Approach to Structural Equation Modeling provides
a detailed account of this novel statistical methodology and its
various extensions. The authors present the theoretical
underpinnings of generalized structured component analysis and
demonstrate how it can be applied to various empirical examples.
The book enables quantitative methodologists, applied researchers,
and practitioners to grasp the basic concepts behind this new
approach and apply it to their own research. The book emphasizes
conceptual discussions throughout while relegating more technical
intricacies to the chapter appendices. Most chapters compare
generalized structured component analysis to partial least squares
path modeling to show how the two component-based approaches differ
when addressing an identical issue. The authors also offer a free,
online software program (GeSCA) and an Excel-based software program
(XLSTAT) for implementing the basic features of generalized
structured component analysis.
The volume represents presentations given at the 86th annual
meeting of the Psychometric Society, held virtually on July 19-23,
2021. About 500 individuals contributed paper presentations,
symposiums, poster presentations, pre-conference workshops, keynote
presentations, and invited presentations. Since the 77th meeting,
Springer has published the conference proceedings volume from this
annual meeting to allow presenters to share their work and ideas
with the wider research community, while still undergoing a
thorough review process. This proceedings covers a diverse set of
psychometric topics, including item response theory, Bayesian
models, reliability, longitudinal measures, and cognitive
diagnostic models.
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