Kenneth A.Bollen – Latent Curve Models

DESCRIPTION

Data analysis in the social sciences is done using an effective technique.

The need for this timely publication is highlighted by the recent explosion in longitudinal data in the social sciences. Latent curve models can be analyzed using a Structural Equation Perspective. Random intercepts and slopes allow each case in a sample to have a different trajectory over time. Variables can be used to predict the parameters governing the trajectory.

The authors provide original results when they combine a lot of research and findings. The book looks at LCMs from the perspective of structural equation models. Simple regression-based procedures that are useful in the early stages of LCMs are not the only ones discussed in the presentation. 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, and establishes the identification of a variety of LCMs.

This text has been thoroughly class-tested and makes extensive use of educational 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

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

TABLE OF CONTENTS

Preface.

There is an introduction.

There is a Conceptualization and Analysis of Trajectories.

There are three initial questions aboutjectories.

The Latent Curve Models have a brief history.

There is an organization of the book.

There are 2 models of the Latent Curve model.

There are repeated measures.

There is a general model and assumptions.

There is a 2.3 identification.

There is a case-by-case approach.

There is a Structural Equation Model Approach.

There are alternative approaches to theSEM.

Conclusions.

Test Statistics, Nonnormality, and Statistical Power are included in Appendix 2A.

There are missing data and alternative metrics of time.

There is missing data.

There are missing data and alternative metrics of time.

3.3Conclusions.

The Coding of Time and 4 Nonlinear Trajectories.

The function of time is modeled.

The estimated factor loadings of the curve fitting.

Linear Trajectory Models are 4.3 pieceswise.

There are alternative parametric functions.

The Metric of Time has 4.5 Linear Transformations.

Conclusions.

The Latent Curve Models are identified in Appendix 4A.

There is a Quadratic LCM.

The piecewise LCM is 4A.2

There are 5 Latent Curve models.

There is a model and assumptions.

The identification is 5.2.

Structural Equation Modeling Approach.

Interpretation of model estimates

There is an empirical example.

There are 5.6Conclusions.

The analysis of groups.

There is a dummy variable approach.

There is a multiple-group analysis.

Group membership is unknown.

There were 6.4Conclusions.

There is a case-by-case approach to analyzing various groups.

There is a dummy variable method.

Multiple-group analysis

Group membership unknown.

Appendix Summary

There are 7 Latent Curve Models.

There are time-invariant covariates.

There are time-variables.

There is simultaneous inclusion of time-invariant and time-varying covariates.

There are Multivariate Latent Curve Models.

The model is called 7.5 autoregressive Latent Trajectory.

All models have a general equation.

There aremplied Moment Matrices.

There were 7.8Conclusions.

There are 8 extensions of the Latent Curve Models.

The measures are repeated.

Multiple Indicators with Repeated Latent Variables.

There are 8 Latent Covariates.

Conclusions.

There are references.

There is an author index.

The subject index.

AUTHOR INFORMATION

KENNETH A. BOLLEN. The Director of the Odum Institute for Research in Social Science is also an Adjunct Professor of Statistics at The University of North Carolina at Chapel Hill. Structural Equations with Latent Variables is one of the books he has written.

PatRICK J. CURRAN was killed in the line of duty. The University of North Carolina at Chapel Hill has an Associate Professor of Psychology. Through his program of research, writing, and teaching, he has made contributions to the development and application of new quantitative methodologies in the social sciences.