Amsterdam University of Applied Sciences
Longitudinal Research with Latent Variables
van Montfort, C.A.G.M.; Oud, Han; Satorra, Albert
Publication date 2010
Document Version Final published version
Link to publication
Citation for published version (APA):
van Montfort, C. A. G. M., Oud, H., & Satorra, A. (2010). Longitudinal Research with Latent Variables. Springer.
General rights
It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons).
Disclaimer/Complaints regulations
If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please contact the library:
https://www.amsterdamuas.com/library/contact/questions, or send a letter to: University Library (Library of the University of Amsterdam and Amsterdam University of Applied Sciences), Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible.
Download date:27 Nov 2021
Copyright © 2007 by Lawrence Erlbaum Associates, Inc.
All rights reserved. No part of this book may be reproduced in any form, by photostat, microfilm, retrieval system, or
any other means, without prior written permission of the publisher.
Lawrence Erlbaum Associates, Inc., Publishers 10 Industrial Avenue
Mahwah, NJ 07430
Cover design by Tomai Maridou
Library of Congress Cataloging-in-Publication Data
Longitudinal models in the behavioral and related sciences / edited by Kees van Montfort, Johan Oud, Albert Satorra.
Includes bibliographical references.
ISBN 0-8058-5913-6 (case: alk. paper) 1. Psychology--Mathematical models.
I. Montfort, Kees van. II. Oud, Johan. III. Satorra, Albert BF39.L58 2007
300.1'1--dc22 2006017399
Books published by Lawrence Erlbaum Associates are printed on acid-free paper, and their bindings are chosen for strength and durability.
Contents
Contributors……….... ix Preface……….... xv
PART 1: THEORETICAL DEVELOPMENTS
1. Latent Markov Models for Categorical Variables and Time- Dependent Covariates
Ab Mooijaart and Kees van Montfort……….. 1
2. Comparison of Four Procedures to Estimate the Damped Linear Differential Oscillator for Panel Data
Johan Oud………... 19
3. Modeling the Coevolution of Networks and Behavior Tom Snijders, Christian Steglich and Michael Schweinberger...………... 41
4. Stochastic Differential Equation Models With Sampled Data Hermann Singer……….…….... 73
v
vi Contents
5. Factor Score and Parameter Estimation in Nonlinear Dynamical Systems Models
Sy-Miin Chow……….………... 107
6. Growth Models for Categorical Response Variables: Standard, Latent-Class, and Hybrid Approaches
Jeroen Vermunt…….………... 139
7. Dynamic Structural Equation Modeling in Longitudinal Experimental Studies
John J. McArdle………... 159
8. A Second-Order Structured Latent Curve Model for Longitudinal Data
Shelley Blozis……….………... 189
PART 2: APPLICATIONS
9. Patterns of Persistence of Abnormal Returns: A Finite Mixture Distribution Approach
Juan-Carlos Bou and Albert Satorra………... 215
10. The Development of Deviant and Delinquent Behavior of Adolescents: Applications of Latent Class Growth Curves and Growth Mixtures Models
Jost Reinecke………..………... 239
11. Nonlinear Growth Mixture Models in Research on Cognitive Aging
Kevin J. Grimm, John J. McArdle, and
Fumiaki Hamagami….………... 267
12. Longitudinal Multilevel Modelling: A Comparison of Growth Curve Models and Structural Equation Modelling Using Panel Data From Germany Uwe Engel, Alexander Gattig, and Julia Simonson….……………. 295
13. Applying Autoregressive Cross-Lagged and Latent Growth Curve Models to a Three-Wave Panel Study
Elmar Schlueter, Eldad Davidov, and Peter Schmidt…..………... 315
Contents vii
14. Markov Process Models for Discrimination Learning
Ingmar Visser, Verena Schmittmann, and Maartje E.J. Raijmakers……….………. 337
15. The Use of Covariates in Distance Association Models for the Analysis of Change
Mark de Rooij…………………. 367
16. Multitrait-Multimethod Models for Longitudinal Research Annette Scherpenzeel and Willem Saris………………… 381
17. Patterns of House-Price Inflation in New Zealand
Nick Longford, I. McCarthy, and G. Dowse…………..……..…… 403 Author index ………..….… 435 Subject index ………...………... 443
Contributors
Shelley A. Blozis
University of California, Department of Psychology, One Shields Avenue, Davis, CA 95616
United States of America Email: sablozis@ucdavis.edu
Juan-Carlos Bou
Universitat Jauma I, Business Administration and Marketing, Avda. Sos Baynat, S/N, Castellon 12071
Spain
Email: bou@emp.uji.es
Sy-Miin Chow
University of Notre Dame, Department of Psychology, 108 Haggar Hall, 46656 Notre Dame
United States of America Email: schow@nd.edu
Eldad Davidov
University of Basel, Department of Sociology, Petersgraben 27, 4051 Basel
Switzerland
Email: eldad.davidov@unibas.ch
ix
Contributors x
Uwe Engel
Univeristy of Bremen, Social Statistics and Research Group, Department of Social Sciences, Celsiusstrasse, Bremen 28359 Germany
Email: uwe.h.engel@t-online.de
Alexander Gattig
Univeristy of Bremen, Social Statistics and Research Group, Department of Social Sciences, Celsiusstrasse, Bremen 28359 Germany
Email: gattig@empas.uni-bremen.de
Kevin J. Grimm
University of Virginia, Department of Psychology, PO Box 400871, Charlottesville, VA 22904-4871 United States of America
Email: kjg5c@cms.mail.virginia.edu
Fumiaki Hamagami
University of Virginia, Department of Psychology, Charlottesville, Virginia
United States of America fh3s@virginia.edu
Nicholas T. Longford
SNTL, Leicester, UK, and Department d’Economia I Empresa
Universitat Pompeu Fabra, Ramon Trias Farga 25-27, 08005 Barcelona Spain
Email: nick.longford@upf.edu
John J. McArdle
University of Soutern California, Department of Psychology, Los Angeles, CA 90089
United States of America jmcardle@usc.edu
Kees van Montfort
Free University Amsterdam and Business University Nyenrode,
Department of Econometrics, De Boelelaan 1105, 1081 HV Amsterdam The Netherlands
Email: kvmontfort@feweb.vu.nl
Contributors xi
Ab Mooijaart
Leiden University, Department of Psychology,
Chair section Method and Statistics, Wassenaarseweg 52, PO Box 9555, 2300 RB Leiden
The Netherlands
Email: mooijaart@fsw.leidenuniv.nl
Johan Oud
Radboud University Nijmegen, Behavioral Science Insititute, Gerrit van Durenstraat 4, 6525 DT Nijmegen
The Netherlands Email: j.oud@pwo.ru.nl
Maartje E.J. Raijmakers
University of Amsterdam, Department of Psychology, Roetersstraat 15, 1018 WB Amsterdam
The Netherlands
m.e.j.raijmakers@uva.nl
Jost Reinecke
University of Bielefeld, Faculty of Sociology, PO Box 100131, 33501 Bieleveld
Germany
Email: reinecke@uni-trier.de
Mark de Rooij
Leiden University, Methods and Statistics Group,
Department of Psychology, Wassenaarseweg 52, Leiden 2333AK The Netherlands
Email: rooijm@fsw.leidenuniv.nl
Willem Saris
University of Amsterdam, Sociology Department, Kloveniersburgwal 48, Amsterdam 1012 CX The Netherlands
Email: saris030@planet.nl
Albert Satorra
Universitat Pompeu Fabra, Department d’Economia I Empresa, Ramon Trias Fargas 25-27, 08005 – Barcelona
Spain
Email: albert.satorra@upf.edu
Contributors xii
Annette Scherpenzeel
University of Amsterdam, Sociology Department, Kloveniersburgwal 48, Amsterdam 1012 CX, The Netherlands
Email: a.scherpenzeel@planet.nl
Elmar Schlueter
University of Marburg, Department of Psychology, Gutenbergstrasse 18, 35032 Marburg,
Germany
Email: e_schluet@gmx.de
Peter Schmidt
Justus-Liebig-Universitaet, Department of Political Sciences, Giessen
Germany
Email: Schmidt.braunfels@t-online.de
Verena Schmittmann
University of Amsterdam, Department of Developmental Psychology, Roetersstraat 15, Amsterdam 1018 WB
The Netherlands
Email: v.d.schmittmann@uva.nl
Julia Simonson
University of Bremen, Social Statistics and Research Group, Department of Social Sciences, Celsiusstrasse, Bremen 28359 Germany
Email: simonson@uni-bremen.de
Herman Singer
Fern Universitaet in Hagen,
Department of Statistics and Methods of Social Research, Universitaetsstr. 41, D- 58084 Hagen
Germany
Email: hermann.singer@fernuni-hagen.de
Tom Snijders
University of Groningen, ICS/Department of Sociology, Grote Rozenstraat 31, 9721 JL Groningen
The Netherlands
Email: t.a.b.snijders@ppsw.rug.nl
Contributors xiii
Christian Steglich
University of Groningen, ICS/Department of Sociology, Grote Rozenstraat 31, 9721 JL Groningen
The Netherlands
Email: c.e.g.steglich@rug.nl
Jeroen Vermunt
Tilburg University, Department of Methodlogy and Statistics, Warandalaan 2, 5037AB Tilburg
The Netherlands
Email: j.k.vermunt@uvt.nl
Ingmar Visser
University of Amsterdam, Department of Psychology, Roetersstraat 15, Amsterdam 1018 WB
The Netherlands Email: i.visser@uva.nl
xv
Preface
Over the past decade there has become widespread agreement that serious causal analysis should be based on longitudinal data. The longitudinal models and analysis procedures in this book are written by experts in the field and represent current longitudinal approaches in the behavioral and related sciences. Divided into two parts, Theoretical Developments and Applications, the book is intended for methodologists and statisticians who use longitudinal analysis. The book reviews various models that are used in the behavioral and related sciences (psychology, sociology, education, economics, management, and medical sciences) and the technical problems involved in their formulations. In addition, the contents offer researchers new ideas about the use of longitudinal analysis in solving problems that arise due to the specific nature of the design and data available.
The first part of the book demonstrates the latest theoretical developments. Chapters 1 and 6 address problems that arise due to the categorical nature of the data available. Chapters 2, 4, and 5 deal with issues related to continuous observation processes such as the damped differential oscillator, stochastic differential equations, and nonlinear dynamic systems.
Chapter 3 considers problems arising when network analysis is extended to longitudinal data and Chapter 7 considers statistical modeling problems associated with grown-curve data.
The second part of the book, the applied chapters, demonstrates how specific problems of empirical research with longitudinal data can be solved.
Chapter 9 deals with heterogeneity on the patterns of a firm’s profit; Chapter 17, patterns of house prices; Chapter 10 discusses delinquent behavior of adolescents; Chapter 11, nonlinearity in growth in assessing cognitive aging;
Chapter 13 is concerned with cross-lagged effects in authoritarianism;
xvi Preface
Chapter 16, measurement error issues in longitudinal research; and Chapter 15 addresses distance association for the analysis of change. The second part demonstrates that applying longitudinal modeling should be done with great caution, not only on the statistical side, such as the use of new methods for finite mixture modeling, but also regarding the interpretation of the results.
We thank the authors for their willingness to contribute to the book, the reviewers for their expertise and time invested, and Lawrence Erlbaum for their decision to publish the book and giving it a place in the European Association of Methodology (EAM) book series.
Kees van Montfort, Han Oud and Albert Satorra
