"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, 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
Part I: Introduction to Intensive Longitudinal Methods. What Are Intensive Longitudinal Methods? Applications of Intensive Longitudinal Methods. Why Use Intensive Longitudinal Methods? Goals for This Book and Intended Audience. Organization of This Book. Recommended Readings. Part II: Types of Intensive Longitudinal Designs. Chapter Overview. Strengths of Intensive Longitudinal Designs. Types of Research Questions. Types of Designs and Prototypical Examples. Limitations of Intensive Longitudinal Designs. Which Intensive Longitudinal Design Is Best For You? Recommended Readings. Part III: Fundamentals of Intensive Longitudinal Data. Chapter Overview. An Example Dataset. Between-Subjects and Within-Subjects Levels of Analysis. Allowing for Between-Subjects Heterogeneity: Random Effects. Taking Account of Time. How Many Independent Units Are There in Intensive Longitudinal Datasets? Choosing an Appropriate Zero Point For X. Recommended Readings. Part IV: Modeling the Time Course of Continuous Outcomes. Chapter Overview. The Example Intervention Dataset. An Application of Linear Growth Curve Analysis. Example Write-Up of Intervention Study Data. Chapter Summary. Recommended Readings. Part V: Modeling the Within-Subject Causal Process. Chapter Overview. Conceptualizing a Within-Subject Causal Process. Example Daily Conflict and Intimacy Dataset. Multilevel Causal Model Linking Daily Conflict and Intimacy. Modeling a Process with Missing Repeated Measures Data. When the Intervals between Measurements Are Unequal. Example Write-Up of Daily Conflict Study Data. Recommended Readings. Part VI: Modeling Categorical Outcomes. Chapter Overview. Exploring the Example Dataset. A Longitudinal Multilevel Model Linking Morning Anger to the Incidence of Daily Conflict in Couples. Implementation in SAS PROC GLIMMIX. Implementation in IBM SPSS GENLINMIXED. Implementation in Mplus. Chapter Summary. Recommended Readings. Part VII: Psychometrics of Intensive Longitudinal Measures of Emotional States. Chapter Overview. Basic Ideas about Random Measurement Error. Making Use of Generalizability Theory. Making Use of Multilevel Confirmatory Factor Analysis. Chapter Summary. Recommended Readings. Part VIII: Design and Analysis of Intensive Longitudinal Studies of Distinguishable Dyads. Chapter Overview. Motivation for Studying the Everyday Lives of Dyads. Methodological and Design Issues in Intensive Longitudinal Studies of Distinguishable Dyads. The Multilevel Model for Intensive Longitudinal Data from Distinguishable Dyads.Example Write-Up of Dyadic Study Data. Recommended Readings. Part IX: Within-Subject Mediation Analysis. Chapter Overview. Single-Level Mediation to Multilevel Mediation. Empirical Example. Implementing Within-Subject Mediation in Statistical Software. Interpretation of Results. Chapter Summary. Recommended Readings. Part X: Statistical Power for Intensive Longitudinal Designs. Chapter Overview. Approaches to Power. Power in Multilevel Models. Power for the Marital Therapy and Intimacy Example. Power for the Daily Conflicts and Intimacy Example. Power Analysis for the Daily Conflict Categorical Outcomes Example. Power for the Dyadic Process Example. Power for the Within-Subject Multilevel Mediation Example. Chapter Summary. Recommended Readings.