Kenneth A.Bollen – Latent Curve Models

Description

Kenneth A.Bollen – Latent Curve Models

Description

An efficient method for information evaluation within the social sciences

The current explosion in longitudinal information within the social sciences highlights the necessity for this well timed publication. Latent Curve Models: A Structural Equation Perspective gives an efficient method to investigate latent curve fashions (LCMs). This kind of knowledge options random intercepts and slopes that allow every case in a pattern to have a special trajectory over time. Furthermore, researchers can embrace variables to foretell the parameters governing these trajectories.

The authors synthesize an unlimited quantity of analysis and findings and, on the similar time, present authentic outcomes. The e-book analyzes LCMs from the attitude of structural equation fashions (SEMs) with latent variables. While the authors talk about easy regression-based procedures which are helpful within the early levels of LCMs, a lot of the presentation makes use of SEMs as a driving device. This cutting-edge work contains a few of the authors’ current work on the autoregressive latent trajectory mannequin, suggests new fashions for methodology components in a number of indicators, discusses repeated latent variable fashions, and establishes the identification of quite a lot of LCMs.

This textual content has been completely class-tested and makes in depth use of pedagogical instruments to assist readers in mastering and making use of LCMs shortly and simply to their very own information units. Key options embrace:

• Chapter introductions and summaries that present a fast overview of highlights
• Empirical examples supplied all through that permit readers to check their newly discovered data and uncover sensible functions
• Conclusions on the finish of every chapter that stress the important factors that readers want to grasp for development to extra subtle subjects
• Extensive footnoting that factors the way in which to the first literature for extra info on explicit subjects

With its emphasis on modeling and using quite a few examples, this is a superb e-book for graduate programs in latent trajectory fashions in addition to a supplemental textual content for programs in structural modeling. This e-book is a superb help and reference for researchers in quantitative social and behavioral sciences who want to investigate longitudinal information.

 

Table of Contents

Preface.

1 Introduction.

1.1 Conceptualization and Analysis of Trajectories.

1.2 Three Initial Questions About Trajectories.

1.3 Brief History of Latent Curve Models.

1.4 Organization of the Remainder of the Book.

2 Unconditional Latent Curve Model.

2.1 Repeated Measures.

2.2 General Model and Assumptions.

2.3 Identification.

2.4 Case-By-Case Approach.

2.5 Structural Equation Model Approach.

2.6 Alternative Approaches to the SEM.

2.7 Conclusions.

Appendix 2A: Test Statistics, Nonnormality, and Statistical Power.

3 Missing Data and Alternative Metrics of Time.

3.1 Missing Data.

3.2 Missing Data and Alternative Metrics of Time.

3.3 Conclusions.

4 Nonlinear Trajectories and the Coding of Time.

4.1 Modeling Nonlinear Functions of Time.

4.2 Nonlinear Curve Fitting: Estimated Factor Loadings.

4.3 Piecewise Linear Trajectory Models.

4.4 Alternative Parametric Functions.

4.5 Linear Transformations of the Metric of Time.

4.6 Conclusions.

Appendix 4A: Identification of Quadratic and Piecewise Latent Curve Models.

4A.1 Quadratic LCM.

4A.2 Piecewise LCM.

5 Conditional Latent Curve Models.

5.1 Conditional Model and Assumptions.

5.2 Identification.

5.3 Structural Equation Modeling Approach.

5.4 Interpretation of Conditional Model Estimates.

5.5 Empirical Example.

5.6 Conclusions.

6 The Analysis of Groups.

6.1 Dummy Variable Approach.

6.2 Multiple-Group Analysis.

6.3 Unknown Group Membership.

6.4 Conclusions.

Appendix 6A: Case-by-Case Approach to Analysis of Various Groups.

6A.1 Dummy Variable Method.

6A.2 Multiple-Group Analysis.

6A.3 Unknown Group Membership.

6A.4 Appendix Summary.

7 Multivariate Latent Curve Models.

7.1 Time-Invariant Covariates.

7.2 Time-Varying Covariates.

7.3 Simultaneous Inclusion of Time-Invariant and Time-Varying Covariates.

7.4 Multivariate Latent Curve Models.

7.5 Autoregressive Latent Trajectory Model.

7.6 General Equation for All Models.

7.7 Implied Moment Matrices.

7.8 Conclusions.

8 Extensions of Latent Curve Models.

8.1 Dichotomous and Ordinal Repeated Measures.

8.2 Repeated Latent Variables with Multiple Indicators.

8.3 Latent Covariates.

8.4 Conclusions.

References.

Author Index.

Subject Index.

 

Author Information

KENNETH A. BOLLEN, PhD, is Henry Rudolph Immerwahr Distinguished Professor of Sociology, Director of the Odum Institute for Research in Social Science, and an Adjunct Professor of Statistics at The University of North Carolina at Chapel Hill. He is the writer of two books, together with Structural Equations with Latent Variables (Wiley), and greater than 100 scholarly papers.

PATRICK J. CURRAN, PhD, is Associate Professor of Psychology within the L. L. Thurstone Psychometric Laboratory at The University of North Carolina at Chapel Hill. He has made contributions to the event and utility of latest quantitative methodologies within the social sciences via his built-in program of analysis, writing, and educating.

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