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Longitudinal data analysis using structural equation models

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Longitudinal data analysis using structural equation models
Preface
Overview
I. Foundations
1.Background and Goals of Longitudinal Research
2.Basics of Structural Equation Modeling
3.Some Technical Details on Structural Equation Modeling
4.Using the Simplified Reticular Action Model Notation
5.Benefits and Problems Using Structural Equation Modeling in Longitudinal Research
II. Longitudinal SEM for the Direct Identification of Intraindividual Changes
6.Alternative Definitions of Individual Changes
7.Analyses Based on Latent Curve Models
8.Analyses Based on Time-Series Regression Models
9.Analyses Based on Latent Change Score Models
10.Analyses Based on Advanced Latent Change Score Models
III. Longitudinal SEM for Interindividual Differences in Intraindividual Changes
11.Studying Interindividual Differences in Intraindividual Changes
12.Repeated Measures Analysis of Variance as a Structural Model
13.Multilevel Structural Equation Modeling Approaches to Group Differences
14.Multiple Group Structural Equation Modeling Approaches to Group Differences
15.Incomplete Data With Multiple Group Modeling of Changes
IV. Longitudinal SEM for the Interrelationships in Growth
16.Considering Common Factors/Latent Variables in Structural Models
17.Considering Factorial Invariance in Longitudinal Structural Equation Modeling
18.Alternative Common Factors With Multiple Longitudinal Observations
19.More Alternative Factorial Solutions for Longitudinal Data
20.Extensions to Longitudinal Categorical Factors
V. Longitudinal SEM for Causes (Determinants) of Intraindividual Changes
21.Analyses Based on Cross-Lagged Regression and Changes
22.Analyses Based on Cross-Lagged Regression in Changes of Factors
23.Current Models for Multiple Longitudinal Outcome Scores
24.The Bivariate Latent Change Score Model for Multiple Occasions
25.Plotting Bivariate Latent Change Score Results
VI. Longitudinal SEM for Interindividual Differences in Causes (Determinants) of Intraindividual Changes
26.Dynamic Processes Over Groups
27.Dynamic Influences Over Groups
28.Applying a Bivariate Change Model With Multiple Groups
29.Notes on the Inclusion of Randomization in Longitudinal Studies
30.The Popular Repeated Measures Analysis of Variance
VII. Summary and Discussion
31.Contemporary Data Analyses Based on Planned Incompleteness
32.Factor Invariance in Longitudinal Research
33.Variance Components for Longitudinal Factor Models
34.Models for Intensively Repeated Measures
35.Coda: The Future Is Yours!
References
Index
About the Authors

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