Intensive Longitudinal Methods : An Introduction to Diary and Experience Sampling Research book cover
1st Edition

Intensive Longitudinal Methods
An Introduction to Diary and Experience Sampling Research

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ISBN 9781462506781
Published April 9, 2013 by Guilford Press
256 Pages

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Book Description

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

1. Introduction 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
2. Types of Intensive Longitudinal Designs
2.1 Chapter Overview
2.2 Strengths of Intensive Longitudinal Designs
2.3 Types of Research Questions
2.4 Types of Designs and Prototypical Examples
2.5 Limitations of Intensive Longitudinal Designs
2.6 Which Intensive Longitudinal Design Is Best for You?
2.7 Chapter Summary
2.8 Recommended Readings
3. Fundamentals of Intensive Longitudinal Data
3.1 Chapter Overview
3.2 An Example Dataset
3.3 Between-Subjects and Within-Subjects Levels of Analysis
3.4 Allowing for Between-Subjects Heterogeneity: Random Effects
3.5 Taking Account of Time
3.6 How Many Independent Units Are There in Intensive Longitudinal Datasets?
3.7 Choosing an Appropriate Zero Point For X
3.8 Chapter Summary
3.9 Recommended Readings
4. Modeling the Time Course of Continuous Outcomes
4.1 Chapter Overview
4.2 The Example Intervention Dataset
4.3 An Application of Linear Growth Curve Analysis
4.4 Example Write-Up of Intervention Study Data
4.5 Chapter Summary
4.6 Recommended Readings
5. Modeling the Within-Subject Causal Process
5.1 Chapter Overview
5.2 Conceptualizing a Within-Subject Causal Process
5.3 Example Daily Conflict and Intimacy Dataset
5.4 Multilevel Causal Model Linking Daily Conflict and Intimacy
5.5 Modeling a Process with Missing Repeated Measures Data
5.6 When the Intervals between Measurements Are Unequal
5.7 Example Write-Up of Daily Conflict Study Data
5.8 Chapter Summary
5.9 Recommended Readings
6. Modeling Categorical Outcomes
6.1 Chapter Overview
6.2 Exploring the Example Dataset
6.3 A Longitudinal Multilevel Model Linking Morning Anger to the Incidence of Daily Conflict in Couples
6.4 Implementation in SAS PROC GLIMMIX
6.5 Implementation in IBM SPSS GENLINMIXED
6.6 Implementation in Mplus
6.7 Chapter Summary
6.8 Recommended Readings
7. Psychometrics of Intensive Longitudinal Measures of Emotional States
7.1 Chapter Overview
7.2 Basic Ideas about Random Measurement Error
7.3 Making Use of Generalizability Theory
7.4 Making Use of Multilevel Confirmatory Factor Analysis
7.5 Chapter Summary
7.6 Recommended Readings
8. Design and Analysis of Intensive Longitudinal Studies of Distinguishable Dyads
8.1 Chapter Overview
8.2 Motivation for Studying the Everyday Lives of Dyads
8.3 Methodological and Design Issues in Intensive Longitudinal Studies of Distinguishable Dyads
8.4 The Multilevel Model for Intensive Longitudinal Data from Distinguishable Dyads
8.5 Example Write-Up of Dyadic Study Data
8.6 Chapter Summary
8.7 Recommended Readings
9. Within-Subject Mediation Analysis
9.1 Chapter Overview
9.2 Single-Level Mediation to Multilevel Mediation
9.3 Empirical Example
9.4 Implementing Within-Subject Mediation in Statistical Software
9.5 Interpretation of Results
9.6 Chapter Summary
9.7 Recommended Readings
10. Statistical Power for Intensive Longitudinal Designs
10.1 Chapter Overview
10.2 Approaches to Power
10.3 Power in Multilevel Models
10.4 Power for the Marital Therapy and Intimacy Example
10.5 Power for the Daily Conflicts and Intimacy Example
10.6 Power Analysis for the Daily Conflict Categorical Outcomes Example
10.7 Power for the Dyadic Process Example
10.8 Power for the Within-Subject Multilevel Mediation Example
10.9 Chapter Summary
10.10 Recommended Readings

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Niall Bolger, PhD, is Professor and Chair of Psychology at Columbia University. He is a Charter Member and Fellow of the Association for Psychological Science and a Fellow of the Society of Experimental Social Psychology and the Society for Personality and Social Psychology. Dr. Bolger's main research interests include adjustment processes in close relationships using intensive longitudinal methods and laboratory-based studies of dyadic behavior, emotion and physiology, and personality processes as they are revealed in patterns of behavior, emotion, and physiology in daily life. He is also interested in statistical methods for analyzing longitudinal and multilevel data.

Jean-Philippe Laurenceau, PhD, is Professor of Psychology at the University of Delaware. He is an appointed member of the Social, Personality, and Interpersonal Processes grant review panel of the National Institutes of Health. Dr. Laurenceau's research focuses on understanding the processes by which partners in marital and romantic relationships develop and maintain intimacy in the context of everyday life. His methodological interests include intensive longitudinal methods for studying close relationship processes and applications of modern methods for the analysis of change in individuals and dyads.


"Because they allow researchers to understand within-person processes in natural settings, intensive longitudinal methods are essential tools for building a science of the individual. Bolger and Laurenceau do a superb job of taking readers through the mechanics of research design, data analysis, and interpretation, enabling readers to tackle important questions about 'who we are' in depth and detail. I highly recommend Bolger and Laurenceau's book for those wishing to learn and use these powerful methods."--Walter Mischel, PhD, Niven Professor of Humane Letters in Psychology, Columbia University

"In a remarkably short period of time, intensive longitudinal designs have become a staple of the behavioral scientist's toolbox, yet researchers do not always know how to make the most of their data. This is the book we have been waiting for. Bolger and Laurenceau have written a complete, authoritative, and highly accessible volume that is sure to set the standard for years to come. Researchers and students will find this landmark volume to be an essential resource."--Harry T. Reis, PhD, Department of Clinical and Social Sciences in Psychology, University of Rochester

"Bolger and Laurenceau have put together a fantastic primer. The well-crafted and clearly explained background, examples, datasets, and programming codes make this a go-to book for learning how to prepare, analyze, and make the most of intensive longitudinal data. Both instructors and students will appreciate the straightforward, highly readable format. This book's pages are sure to get well worn."--Nilam Ram, PhD, Department of Human Development and Family Studies and Department of Psychology, The Pennsylvania State University

"A valuable and immensely practical resource from two of the world's intensive longitudinal masters. This book is a 'must read' for researchers. Each chapter provides detailed, step-by step guidance on basic to advanced analytic techniques, including exemplar data sets, visual imagery, complete statistical code, and sample write-ups. From spaghetti plots to power analysis, with Bolger and Laurenceau as expert guides, researchers will learn what to do, how to do it, and how to write it up."--Tamlin S. Conner, PhD, Department of Psychology, University of Otago, New Zealand

"This book details exactly how to analyze data gathered from diary and experience sampling studies. In clear language and with real data, it explains how to use multilevel modeling to answer common types of research questions. To make the presentation complete, syntax for SPSS, SAS, and Mplus is provided. Researchers and graduate students conducting studies of daily life will find this book indispensable. I would use it as a text in a graduate-level research methods class and as a resource when designing and conducting my own analyses."--Joel M. Hektner, PhD, Department of Human Development and Family Science, North Dakota State University

"This book couldn’t have come at a better time. All too often, investigators are not sure how to deal with the vast amounts of data they collect using diary methods, and do not fully appreciate the strengths and limitations of their data. This book, in my opinion, is the cure."--Howard Tennen, PhD, Department of Community Medicine and Health Care, University of Connecticut Health Center

"Intensive longitudinal research yields uniquely rich data, but the analyses quickly get complex. Bolger and Laurenceau give researchers the necessary tools and knowledge to conduct and analyze their own intensive longitudinal studies. Using to-the-point explanations and helpful, realistic examples, the book goes step by step through everything there is to know, from the very basics to advanced data-analytic issues--and does so in a delightfully engaging manner."--Matthias R. Mehl, PhD, Department of Psychology, University of Arizona

"The book addresses cutting-edge quantitative approaches to within-subject causal modeling of change while illustrating how researchers can combine rich qualitative data with powerful mixed-modeling approaches. I will definitely use this book in extending my own research related to these types of scenarios."--Larry R. Price, PhD, Director, Initiative for Interdisciplinary Research Design and Analysis, Texas State University

-“A clear, straightforward and exceedingly practical text….In each chapter the authors attentively integrate theory, including links to published studies, with meticulous instruction, comprising example datasets and code for the major statistical software packages….Highly valuable to any researcher (PhD upwards), in particular at the stage of writing a research proposal.”--The Psychologist, 11/1/2013ƒƒ“One of the advantages of intensive longitudinal designs is that they allow for an in-depth analysis of how various psychological processes operate within a person….Overall, we found this volume to be very approachable, fast-paced, and interesting….Not only do the authors do an excellent job of explaining how intensive longitudinal data can be modeled, they also provide step-by-step instructions on how to do so….We found it extremely easy to follow along with the examples provided in the text. Researchers who are interested in learning how to use these methods will be able to follow the examples easily and adapt the syntax for their own purposes. Moreover, as an additional instructional tool, the authors provide examples of how to report results for a journal article, providing clear templates and thorough explanations of what kinds of information should be reported and how to do so….Many authors of methodological books struggle to find the right balance between explaining technical matters in a way that can be understood by newcomers, but without sweeping too much of the technical details under the rug. Bolger and Laurenceau strike this balance perfectly. The volume contains valuable introductory chapters that explain the rationale behind the statistical models, the motivation for using intensive longitudinal designs, and some excellent examples….Indeed, it is the chapters on psychometrics (Chapter 7) and statistical power (Chapter 10) that really make this volume shine….Valuable to both younger and seasoned researchers.”--Journal of Social Psychology, 1/1/2014ƒƒ“The book is a welcome addition to the Guilford Press Methodology in the Social Sciences book series. Overall, the book provides a cogent overview of the methodology, including modern applications to research and intervention, and its practical impact. Examples of longitudinal data collection, analysis, and reportage are generously dispersed throughout the book in a fresh, jargon-free, and self-contained format….Takes the methodological challenges seriously and endeavors to provide the reader with a generous cache of reporting techniques to best represent the data and answer the relevant research questions without compromising intelligibility or reliability….An excellent textbook, with over 200 empirical references supporting its contents….Additionally, the authors include several chapter-specific appendices presenting data sets and syntax for a wide selection of statistical software packages….I…would recommend this textbook for advanced graduate courses, and as a necessary tool for researchers interested or engaged in intensive longitudinal design, or those seeking to incorporate the method for grant preparation, ongoing research, program and practice evaluation, and publication.”--Research on Social Work Practice, 9/19/2013ƒƒProvides an in-depth and integrated treatment of the subject that focuses on related applications of a single analytical approach, namely multilevel modeling….[T]here is much here of value for anyone who is engaged in observational research using [intensive longitudinal methods (ILM)]. Written with minimal statistical notation and a highly readable style, this is an accessible and practical introduction to multilevel modeling of [intensive longitudinal data (ILD)]….[T]he book provides valuable guidance on everything from preparing data for analysis through writing up the methods and results in manuscript form. The example data sets are available from a companion web site and computer code is provided for several common statistical packages….[T]he authors have successfully achieved their aims of providing a practical introduction to multilevel modeling of ILD. The book is particularly appropriate for behavioral scientists, but the methods described here apply to any situation in which the focus is modeling within-subject processes, and should have broad, cross-disciplinary appeal. For educators, the book would also make a fine text for a course on advanced longitudinal data analysis.--Journal of American Statistical Association, 11/13/2014