This book has been replaced by Longitudinal Structural Equation Modeling, Second Edition, ISBN 978-1-4625-5314-3.

Table of Contents:
PROLOGUE * A personal introduction and what to expect How statistics came into my life My approach to the book Key features of the book Overview of the book * Datasets and measures used My dataset with the Inventory Felt Energy and Emotion in Life (I FEEL) measure The I FEEL Gallagher and Johnson's MIDUS example Neuroticism Negative affect Dorothy Espelage's bullying and victimization examples Peer victimization Substance use Family conflict Family closeness Bullying Homophobic teasing * Overdue gratitude * Prophylactic apologies 1. OVERVIEW AND SEM FOUNDATIONS * An overview of the conceptual foundations of SEM Concepts, constructs, and indicators From concepts to constructs to indicators to good models * Sources of variance in measurement Classical test theorem Expanding classical test theorem * Characteristics of indicators and constructs Types of indicators and constructs Categorical versus metrical indicators and constructs Types of correlation coefficients that can be modeled * A simple taxonomy of indicators and their roles * Rescaling variables * Parceling * What changes and how? * Some advice for SEM programming * Philosophical issues and how I approach research * Summary * Key terms and concepts introduced in this chapter * Recommended readings 2. DESIGN ISSUES IN LONGITUDINAL STUDIES * Timing of measurements and conceptualizing time Cross-sectional design Single-cohort longitudinal design Cross-sequential design Cohort-sequential design Time-sequential design Other validity concerns Temporal design Lags within the interval of measurement Episodic and Experiential Time * Missing data imputation and planned missing designs Missing data mechanisms Recommendations and caveats Planned missing data designs in longitudinal research * Modeling developmental processes in context * Summary * Key terms and concepts introduced in this chapter * Recommended readings 3. THE MEASUREMENT MODEL * Drawing and labeling conventions * Defining the parameters of a construct * Scale setting * Identification * Adding means to the model: Scale setting and identification with means * Adding a longitudinal component to the CFA model * Adding phantom constructs to the CFA model * Summary * Key terms and concepts introduced in this chapter * Recommended Readings 4. MODEL FIT, SAMPLE SIZE, AND POWER * Model fit and types of fit indices Statistical rationale Modeling rationale The longitudinal null model Summary and cautions * Sample Size * Power * Summary * Key terms and concepts introduced in this chapter * Recommended readings 5. THE LONGITUDINAL CFA MODEL * Factorial invariance * A small (nearly perfect) data example Configural factorial invariance Weak factorial invariance Strong factorial invariance Evaluating invariance constraints Model modification Partial invariance * A larger example followed by tests of the latent construct relations Testing the latent construct parameters * An application of a longitudinal SEM to a repeated-measures experiment * Summary * Key terms and concepts introduced in this chapter * Recommended readings 6. SPECIFYING AND INTERPRETING A LONGITUDINAL PANEL MODEL * Basics of a panel model * The basic simplex change process * Building a panel model Covariate/control variables Building the panel model of positive and negative affect * Illustrative examples of panel models A simplex model of cognitive development Two simplex models of non-longitudinal data A panel model of bullying and homophobic teasing * Summary * Key terms and concepts introduced in this chapter * Recommended readings 7. MULTIPLE-GROUP MODELS * Multiple-group longitudinal SEM Step 1: Estimate missing data and evaluate the descriptive statistics Step 2: Perform any supplemental analysis to rule out potential confounds Step 3: Fit an appropriate multiple-group longitudinal null model Step 4: Fit the configurally invariant model across time and groups Step 5: Test for weak factorial (loadings) invariance Step 6: Test for strong factorial invariance Step 7: Test for mean-level differences in the latent constructs Step 8: Test for the homogeneity of the variance–covariance matrix among the latent constructs Step 9: Test the longitudinal SEM model in each group * A dynamic p-technique multiple-group longitudinal model * Summary * Key terms and concepts introduced in this chapter * Recommended readings 8. MULTILEVEL GROWTH CURVES AND SEM * Longitudinal growth curve model * Multivariate growth curve models * Multilevel longitudinal model * Summary * Key terms and concepts introduced in this chapter * Recommended readings 9. MEDIATION AND MODERATION * Making the distinction between mediators and moderators Cross-sectional mediation Half-longitudinal mediation Full longitudinal mediation * Moderation * Summary * Key terms and concepts introduced in this chapter * Recommended readings 10. JAMBALAYA: COMPLEX CONSTRUCT REPRESENTATIONS AND DECOMPOSITIONS * Multitrait-multimethod models * Pseudo-MTMM models * Bifactor and higher order factor models * Contrasting different variance decompositions * Digestif * Key terms and concepts introduced in this chapter * Recommended readings