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Intensive Longitudinal Methods: An Introduction to Diary and Experience Sampling Research (Methodology in the Social Sciences) 1st Edition

5.0 out of 5 stars 11 customer reviews
ISBN-13: 978-1462506781
ISBN-10: 146250678X
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  • Intensive Longitudinal Methods: An Introduction to Diary and Experience Sampling Research (Methodology in the Social Sciences)
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Editorial Reviews

Review

 

"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 2013-11-01)

“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 2014-01-01)

“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 2013-09-19)

“Provides 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 2014-11-13)

About the Author

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.
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Product Details

  • Series: Methodology in the Social Sciences
  • Hardcover: 256 pages
  • Publisher: The Guilford Press; 1 edition (February 14, 2013)
  • Language: English
  • ISBN-10: 146250678X
  • ISBN-13: 978-1462506781
  • Product Dimensions: 0.8 x 6.2 x 9.8 inches
  • Shipping Weight: 1.1 pounds (View shipping rates and policies)
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (11 customer reviews)
  • Amazon Best Sellers Rank: #633,934 in Books (See Top 100 in Books)

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Top Customer Reviews

By Todd B. Kashdan VINE VOICE on March 23, 2016
Format: Hardcover Verified Purchase
There are few books on hierarchical linear modeling that transfer from text to data analyses. There are even fewer books that are enjoyable to read (as stat books are difficult to write for the less experienced user). This book succeeds on all levels. Easy to read. Immediately helpful. Then there is the added bonus that the authors offer a new, better approach to conducting dyadic analyses. Also, the authors offer suggestions for how to write up the analyses in a meaningful way.

I require all of my graduate students to pick this up.
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Very accessible introduction to generating mixed models. Niall Bolger and Jean-Phillipe Laurenceau did a great job with this book. I only wish it had code for R. Perhaps this will be added to the companion website soon.
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Format: Hardcover
I've been doing experience-sampling research for 10 years, and I was more than a little curious to read this book, which has sparked a lot of buzz in methodological circles. As a young field, experience-sampling lacks a clear statement of "best practices" and "gold standards." How do you estimate power for these weird nested designs? What are good ways to estimate lagged effects? Should you include or ignore time when it isn't a variable of substantive interest?

Anyhow, this grizzled old dog learned some new tricks from this eye-opening book. The text lays out a rationale for good practices for statistical analysis, power analysis, and reporting results in papers. It makes clear much that was foggy, and it was exactly what I had hoped to find when I got started a decade ago. If you're planning a study or submitting a grant proposal that involves intensive assessment, you should read this book first.
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This book is great! As a novice EMA researcher, Drs. Bolger and Laurenceau were clear and thorough about how to analyze an intensive longitudinal study. I am in the beginning stages of developing an EMA study and started to use their power analysis chapter (CH 10) for some post hoc power analyses. Anyone who wants to do an intensive longitudinal study will need CH 10 to write a grant.

If you are just beginning to study intensive longitudinal research, this book is for you. It's straightforward throughout the book. You can also practice each type of analysis by going to their website and using their supplemental material.

If you already have experience with intensive longitudinal design, this book still has a lot of material to refer to and some alternatives for analyzing measures or running a power analysis. They also explain the differences between how Mplus would test a mediation and SAS.

I recommend this book if you are serious about using intensive longitudinal methods.
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Format: Hardcover
This book is simply amazing. I got copies for myself and my staff and we could not put it down. We kept reading it and saying to each "this is a really good book!" It is an excellent, readable, and finally an explanation that I can follow and that makes sense of multilevel models and how to apply them to the type of primarily within-subject design that diary studies tend to be. There are very useful chapters on categorical data, measurement, and power analysis, in addition to clearly explained chapters using continuous variables. Each chapter has code in SAS, SPSS, and Mplus. Their webpage has more software packages. This is the book that should be in the toolkit of everyone doing event-level data analysis.
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This is THE go-to resource for designing and analyzing experience sampling / ecological momentary assessment studies. The authors present challenging material clearly and provide a wealth of additional resources to data analysts to implement their models using a variety of stats packages, including SPSS, SAS, R, HLM and Mplus. I would highly recommend this book to everyone from beginning students to more advanced researchers. Thanks to the authors for putting together such a valuable resource!
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