Intensive Longitudinal Methods An Introduction to Diary and Experience Sampling Research 1st Edition Niall Bolger, Jean Philippe Laurenceau 146250678X 9781462506781

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Product details:

ISBN 10: 146250678X 

ISBN 13: 9781462506781

Author: Niall Bolger, Jean-Philippe Laurenceau

This book offers a complete, practical guide to doing an intensive longitudinal study with individuals, dyads, or groups. It provides the tools for studying social, psychological, and physiological processes in everyday contexts, using methods such as diary and experience sampling. A range of engaging, worked-through research examples with datasets are featured. Coverage includes how to: select the best intensive longitudinal design for a particular research question, apply multilevel models to within-subject designs, model within-subject change processes for continuous and categorical outcomes, assess the reliability of within-subject changes, assure sufficient statistical power, and more. Several end-of-chapter write-ups illustrate effective ways to present study findings for publication. Datasets and output in SPSS, SAS, Mplus, HLM, MLwiN, and R for the examples are available on the companion website

Table of 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 Between-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 Implementation 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

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Tags: Niall Bolger, Jean Philippe Laurenceau, Longitudinal, Diary