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• Front Matter
• Half Title
• Series Page
• Title Page
• Copyright
• Dedication
• Founding Editor’s Note
• Preface
• Acknowledgments
• Contents
• Chapter 1–Introductive to Intensive Longitudinal Methods
• 1.1 What Are Intensive Longitudinal Methods?
• 1.2 Applications of Intensive Longitudinal Methods
• 1.3 Why Use Intensive Longitudinal Methods?
• 1.4 Goals for This Book and Intended Audience
• 1.5 Organization of This Book
• 1.6 Recommended Readings
• Chapter 2–Types of Intensive Longitudinal Designs
• 2.1 Strengths of Intensive Longitudinal Designs
• 2.2 Types of Research Questions
• 2.3 Types of Designs and Prototypical Examples
• 2.4 Limitations of Intensive Longitudinal Designs
• 2.5 Which Intensive Longitudinal Design Is Best for You?
• 2.6 Chapter Summary
• 2.7 Recommended Readings
• Chapter 3–Fundamentals of Intensive Longitudinal Data
• 3.1 An Example Dataset
• 3.2 Beween-Subjects and Within-Subjects Levels of Analysis
• 3.3 Allowing for Between-Subjects Heterogeneity: Random Effects
• 3.4 Taking Account of Time
• 3.5 How Many Independent Units Are There in Intensive Longitudinal Datasets?
• 3.6 Choosing an Appropriate Zero Point for X
• 3.7 Chapter Summary
• 3.8 Recommended Readings
• Chapter 4–Modeling the Time Course of Continuous Outcomes
• 4.1 The Time Course Dataset
• 4.2 An Application of Linear Growth Curve Analysis
• 4.3 Example Write-Up of Time Course Data
• 4.4 Chapter Summary
• 4.5 Recommended Readings
• Chapter 5–Modeling the Within-Subject Causal Process
• 5.1 Conceptualizing a Within-Subject Causal Process
• 5.2 Example Causal Process Dataset
• 5.3 Multilevel Causal Model Linking Daily Conflict to Intimacy
• 5.4 Modeling a process with Missing Repeated Measurements
• 5.5 When the Intervals between Measurements Are Unequal
• 5.6 Example Write-Up of Causal Process Data
• 5.7 Chapter Summary
• 5.8 Recommended Readings
• Chapter 6–Modeling Categorical Outcomes
• 6.1 Exploring the Categorical Outcomes Dataset
• 6.2 A Longitudinal Multilevel Model Linking Morning Anger to the Incidence of Daily Conflict in Coup
• 6.3 Implementation in SAS PROC GLIMMIX
• 6.4 Implementtation in IBM SPSS GENLINMIXED
• 6.5 Implementation in Mplus
• 6.6 Chapter Summary
• 6.7 Recommended Readings
• Chapter 7–Psychometrics of Intensive Longitudinal Measures of Emotional States
• 7.1 Basic Ideas about Random Measurement Error
• 7.2 Making Use of Generalizability Theory
• 7.3 Making Use of Multilevel Confirmatory Factor Analysis
• 7.4 Chapter Summary
• 7.5 Recommended Readings
• Chapter 8–Design and Analysis of Intensive Longitudinal Studies of Distinguishable Dyads
• 8.1 Motivation for Studying the Everyday Lives of Dyads
• 8.2 Methodological and Design Issues in Intensive Longitudinal Studies of Distinguishable Dyads
• 8.3 The Multilevel Model for Intensive Longitudinal Data from Distinguishable Dyads
• 8.4 Example Write-Up of Dyadic Process Study Data
• 8.5 Chapter Summary
• 8.6 Recommended Readings
• Chapter 9–Within-Subject Mediation Analysis
• 9.1 Single-Level Mediation to Multilevel Mediation
• 9.2 Empirical Example
• 9.3 Implementing Within-Subject Mediation in Statistical Software
• 9.4 Interpretation of Results
• 9.5 Chapter Summary
• 9.6 Recommended Readings
• Chapter 10–Statistical Power for Intensive Longitudinal Designs
• 10.1 Approaches to Power
• 10.2 Power in Multilevel Models
• 10.3 Power for the Time Course Example
• 10.4 Power for the Causal Process Example
• 10.5 Power for the Categorical Outcomes Example
• 10.6 Power for the Dyadic Process Example
• 10.7 Power for the Within-Subject Mediation Example
• 10.8 Chapter Summary
• 10.9 Recommended Readings
• References
• Author Index
• Subject Index
• About the Authors