Table Of ContentLONGITUDINAL ANALYSIS
Longitudinal Analysis provides an accessible, application-oriented treatment of intro-
ductory and advanced linear models for within-person fluctuation and change.
Organized by research design and data type, the text uses in-depth examples to pro-
vide a complete description of the model-building process. The core longitudinal
models and their extensions are presented within a multilevel modeling framework,
paying careful attention to the modeling concerns that are unique to longitudinal
data. Written in a conversational style, the text provides verbal and visual interpre-
tation of model equations to aid in their translation to empirical research results.
Overviews and summaries, boldfaced key terms, and review questions will help
readers synthesize the key concepts in each chapter.
Written for non-mathematically oriented readers, this text features:
• A description of the data manipulation steps required prior to model estima-
tion so readers can more easily apply the steps to their own data.
• An emphasis on how the terminology, interpretation, and estimation of famil-
iar general linear models relate to those of more complex models for longitudi-
nal data.
• Integrated model comparisons, effect sizes, and statistical inference in each
example to strengthen readers’ understanding of the overall model-building
process.
• Sample results sections for each example to provide useful templates for pub-
lished reports.
• Examples using both real and simulated data in the text, along with syntax and
output for SAS, SPSS, STATA, and Mplus at www.PilesOfVariance.com to help
readers apply the models to their own data.
Class-tested at the University of Nebraska–Lincoln and in intensive summer
workshops, this is an ideal text for graduate-level courses on longitudinal analysis
or general multilevel modeling taught in psychology, human development and
family studies, education, business, and other behavioral, social, and health sci-
ences. The book’s accessible approach will also help those trying to learn on their
own. Only familiarity with general linear models (regression, analysis of variance)
is needed for this text.
Lesa Hoffman is the Scientific Director of the Research Design and Analysis Unit
and Associate Professor of Quantitative Methods in the Schiefelbusch Institute for
Life Span Studies at the University of Kansas.
MULTIVARIATE APPLICATIONS BOOK SERIES
The Multivariate Applications book series was developed to encourage the use of rig-
orous methodology in the study of meaningful scientific issues and to describe the
applications in easy-to-understand language. The series is sponsored by the Society
of Multivariate Experimental Psychology and welcomes methodological applica-
tions from a variety of disciplines, such as psychology, public health, sociology,
education, and business. Books can be single authored, multiple authored, or edited
volumes. The ideal book for this series would take on one of several approaches:
(1) demonstrate the application of several multivariate methods to a single, major
area of research; (2) describe a multivariate procedure or framework that could be
applied to a number of research areas; or (3) present a discussion of a topic of inter-
est to applied multivariate researchers. Previous books in the series:
What If There Were No Significance Tests? co-edited by Lisa L. Harlow,
Stanley A. Mulaik and James H. Steiger (1997)
Structural Equation Modeling with LISREL, PRELIS, and SIMPLIS: Basic Concepts,
Applications, and Programming by Barbara M. Byrne (1998)
Multivariate Applications in Substance Use Research co-edited by Jennifer S. Rose,
Laurie Chassin, Clark C. Presson, and Steven J. Sherman (2000)
Item Response Theory for Psychologists co-authored by Susan E. Embretson and
Steven P. Reise (2000)
Structural Equation Modeling with AMOS by Barbara M. Byrne (2001)
Conducting Meta-Analysis Using SAS co-authored by Winfred Arthur, Jr.,
Winston Bennett, Jr., and Allen I. Huffcutt (2001)
Modeling Intraindividual Variability with Repeated Measures Data: Methods and
Applications co-edited by D.S. Moskowitz and Scott L. Hershberger (2002)
Multilevel Modeling: Methodological Advances, Issues, and Applications co-edited
by Steven P. Reise and Naihua Duan (2003)
The Essence of Multivariate Thinking: Basic Themes and Methods by
Lisa L. Harlow (2005)
Structural Equation Modeling with EQS: Basic Concepts, Applications, and
Programming, Second Edition by Barbara M. Byrne (2006)
A Paul Meehl Reader: Essays on the Practice of Scientific Psychology co-edited by
Niels G. Waller, Leslie J. Yonce, William M. Grove, David Faust,
Mark F. Lenzenweger (2006)
Introduction to Statistical Mediation Analysis by David P. MacKinnon (2008)
Applied Data Analytic Techniques for Turning Points Research edited by
Patricia Cohen (2008)
Cognitive Assessment: An Introduction to the Rule Space Method by
Kikumi K. Tatsuoka (2009)
Structural Equation Modeling with AMOS: Basic Concepts, Applications, and
Programming, Second Edition by Barbara M. Byrne (2009)
Handbook of Ethics in Quantitative Methodology co-edited by A. T. Panter,
Sonya K. Sterba (2011)
Longitudinal Data Analysis: A Practical Guide for Researchers in Aging, Health, and
Social Sciences co-edited by Jason Newsom, Richard N. Jones, Scott M. Hofer (2011)
Understanding the New Statistics: Effect Sizes, Confidence Intervals, and Meta-Analysis
by Geoff Cumming (2011)
Structural Equation Modeling with Mplus: Basic Concepts, Applications, and
Programming by Barbara M. Byrne (2011)
Frontiers of Test Validity Theory: Measurement, Causation, and Meaning co-authored by
Keith A. Markus, Denny Borsboom (2013)
The Essence of Multivariate Thinking: Basic Themes and Methods, Second Edition by
Lisa L. Harlow (2014)
More information can be obtained from the editor, Lisa L. Harlow, at: Department
of Psy chology, University of Rhode Island, 10 Chafee Rd., Suite 8, Kingston, RI
02881–0808; Phone: 401–874–4242; FAX: 401–874–5562; or E-Mail: [email protected].
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LONGITUDINAL ANALYSIS
Modeling Within-Person Fluctuation
and Change
Lesa Hoffman
First published 2015
by Routledge
711 Third Avenue, New York, NY 10017
and by Routledge
27 Church Road, Hove, East Sussex BN3 2FA
Routledge is an imprint of the Taylor & Francis Group, an informa
business
© 2015 Taylor & Francis
The right of Lesa Hoffman to be identified as the author of this work
has been asserted by her in accordance with sections 77 and 78 of
the Copyright, Designs and Patents Act 1988.
All rights reserved. No part of this book may be reprinted or
reproduced or utilised in any form or by any electronic, mechanical,
or other means, now known or hereafter invented, including
photocopying and recording, or in any information storage or
retrieval system, without permission in writing from the publishers.
Trademark notice: Product or corporate names may be trademarks
or registered trademarks, and are used only for identification and
explanation without intent to infringe.
Library of Congress Cataloging-in-Publication Data
Hoffman, Lesa.
Longitudinal analysis : modeling within-person fluctuation and
change / Lesa Hoffman. — 1 Edition.
pages cm. — (Multivariate applications series)
Includes bibliographical references and index.
1. Longitudinal method. 2. Psychology—Research. I. Title.
BF76.6.L65H64 2014
001.4′33—dc23
2014020352
ISBN: 978-0-415-87600-1 (hbk)
ISBN: 978-0-415-87602-5 (pbk)
ISBN: 978-1-315-74409-4 (ebk)
Typeset in StoneSerif
by Apex CoVantage, LLC
BRIEF CONTENTS
Preface xxi
About the Author xxvii
SECTION I Building Blocks for Longitudinal Analysis 1
CHAPTER 1 Introduction to the Analysis of Longitudinal Data 3
CHAPTER 2 Between-Person Analysis and Interpretation of Interactions 29
CHAPTER 3 Introduction to Within-Person Analysis and Model Comparisons 79
SECTION II Modeling the Effects of Time 111
CHAPTER 4 Describing Within-Person Fluctuation Over Time 113
CHAPTER 5 Introduction to Random Effects of Time and Model Estimation 149
CHAPTER 6 Describing Within-Person Change Over Time 207
SECTION III Modeling the Effects of Predictors 279
CHAPTER 7 Time-Invariant Predictors in Longitudinal Models 281
CHAPTER 8 Time-Varying Predictors in Models of Within-Person Fluctuation 327
CHAPTER 9 Time-Varying Predictors in Models of Within-Person Change 393
SECTION IV Advanced Applications 437
CHAPTER 10 Analysis Over Alternative Metrics and Multiple Dimensions of Time 439
CHAPTER 11 Analysis of Individuals Within Groups Over Time 491
CHAPTER 12 Analysis of Repeated Measures Designs Not Involving Time 551
CHAPTER 13 Additional Considerations and Related Models 591
Author Index 613
Subject Index 617
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CONTENTS
Preface xxi
About the Author xxvii
SECTION I Building Blocks for Longitudinal Analysis 1
CHAPTER 1 Introduction to the Analysis
of Longitudinal Data 3
1. Features of Longitudinal Data 4
1.A. Levels of Analysis: Between-Person and Within-Person
Relationships 4
1.B. A Data Continuum: Within-Person Fluctuation to
Within-Person Change 7
2. Features of Longitudinal Models 9
2.A. The Two Sides of Any Model: Means and Variances 9
2.B. Longitudinal Modeling Frameworks 11
2.C. Data Formats Across Modeling Frameworks 14
2.D. Features of Outcome Variables 15
3. Advantages Over General Linear Models 16
3.A. Modeling Dependency Across Observations 17
3.B. Including Predictors at Multiple Levels of Analysis 19
3.C. Does Not Require the Same Time Observations per Person 20
3.D. Utility for Other Repeated Measures Data 23
3.E. You Already Know How (Even if You Don’t Know It Yet) 23
4. Description of Example Datasets 24
5. Chapter Summary 25
Review Questions 26
References 26
