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  • Author(s) Kenneth A. Bollen / Patrick J. Curran
  • SubtitleA Structural Equation Perspective
  • Edition1
  • Published7th December 2005
  • PublisherJohn Wiley & Sons Inc (US)
  • ISBN9780471455929

A Structural Equation Perspective

An effective technique for data analysis in the social sciences

The recent explosion in longitudinal data in the social sciences
highlights the need for this timely publication. Latent Curve
Models: A Structural Equation Perspective provides an effective
technique to analyze latent curve models (LCMs). This type of data
features random intercepts and slopes that permit each case in a
sample to have a different trajectory over time. Furthermore,
researchers can include variables to predict the parameters
governing these trajectories.


The authors synthesize a vast amount of research and findings
and, at the same time, provide original results. The book analyzes
LCMs from the perspective of structural equation models (SEMs) with
latent variables. While the authors discuss simple regression-based
procedures that are useful in the early stages of LCMs, most of the
presentation uses SEMs as a driving tool. This cutting-edge work
includes some of the authors' recent work on the autoregressive
latent trajectory model, suggests new models for method factors in
multiple indicators, discusses repeated latent variable models, and
establishes the identification of a variety of LCMs.


This text has been thoroughly class-tested and makes extensive
use of pedagogical tools to aid readers in mastering and applying
LCMs quickly and easily to their own data sets. Key features
include:



  • Chapter introductions and summaries that provide a quick
    overview of highlights

  • Empirical examples provided throughout that allow readers to
    test their newly found knowledge and discover practical
    applications

  • Conclusions at the end of each chapter that stress the
    essential points that readers need to understand for advancement to
    more sophisticated topics

  • Extensive footnoting that points the way to the primary
    literature for more information on particular topics


With its emphasis on modeling and the use of numerous examples,
this is an excellent book for graduate courses in latent trajectory
models as well as a supplemental text for courses in structural
modeling. This book is an excellent aid and reference for
researchers in quantitative social and behavioral sciences who need
to analyze longitudinal data.

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  • Author(s) Kenneth A. Bollen / Patrick J. Curran
  • SubtitleA Structural Equation Perspective
  • Edition1
  • Published7th December 2005
  • PublisherJohn Wiley & Sons Inc (US)
  • ISBN9780471455929

A Structural Equation Perspective

An effective technique for data analysis in the social sciences

The recent explosion in longitudinal data in the social sciences
highlights the need for this timely publication. Latent Curve
Models: A Structural Equation Perspective provides an effective
technique to analyze latent curve models (LCMs). This type of data
features random intercepts and slopes that permit each case in a
sample to have a different trajectory over time. Furthermore,
researchers can include variables to predict the parameters
governing these trajectories.


The authors synthesize a vast amount of research and findings
and, at the same time, provide original results. The book analyzes
LCMs from the perspective of structural equation models (SEMs) with
latent variables. While the authors discuss simple regression-based
procedures that are useful in the early stages of LCMs, most of the
presentation uses SEMs as a driving tool. This cutting-edge work
includes some of the authors' recent work on the autoregressive
latent trajectory model, suggests new models for method factors in
multiple indicators, discusses repeated latent variable models, and
establishes the identification of a variety of LCMs.


This text has been thoroughly class-tested and makes extensive
use of pedagogical tools to aid readers in mastering and applying
LCMs quickly and easily to their own data sets. Key features
include:



  • Chapter introductions and summaries that provide a quick
    overview of highlights

  • Empirical examples provided throughout that allow readers to
    test their newly found knowledge and discover practical
    applications

  • Conclusions at the end of each chapter that stress the
    essential points that readers need to understand for advancement to
    more sophisticated topics

  • Extensive footnoting that points the way to the primary
    literature for more information on particular topics


With its emphasis on modeling and the use of numerous examples,
this is an excellent book for graduate courses in latent trajectory
models as well as a supplemental text for courses in structural
modeling. This book is an excellent aid and reference for
researchers in quantitative social and behavioral sciences who need
to analyze longitudinal data.

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