Appropriate for use in developmental research methods or analysis of change courses, this is the first methods handbook specifically designed to meet the needs of those studying development. Leading developmental methodologists present cutting-edge analytic tools and describe how and when to use them, in accessible, nontechnical language. They also provide valuable guidance for strengthening developmental research with designs that anticipate potential sources of bias. Throughout the chapters, research examples demonstrate the procedures in action and give readers a better understanding of how to match research questions to developmental methods. The companion website (www.guilford.com/laursen-materials) supplies data and program syntax files for many of the chapter examples.

Table of Contents:
I. Measurement and Design 1. Foundational Issues of Design and Measurement in Developmental Research, Scott M. Hofer, Valgeir Thorvaldsson, and Andrea M. Piccinin 2. Causal Inference, Identification, and Plausibility, E. Michael Foster 3. Accelerated Longitudinal Designs, Susan C. Duncan and Terry E. Duncan 4. Time-Scale-Dependent Longitudinal Designs, Theodore A. Walls, William D. Barta, Robert S. Stawski, Charles E. Collyer, and Scott M. Hofer 5. Event Frequency Measurement, Brett Laursen, Jaap Denissen, and David F. Bjorklund 6. The Impact of Scaling and Measurement Methods on Individual Differences in Growth, Susan E. Embretson and John Poggio 7. Investigating Factorial Invariance in Longitudinal Data, Roger E. Millsap and Heining Cham II. Approaches to Data Collection 8. Foundational Issues in Longitudinal Data Collection, Lea Pulkkinen and Katja Kokko 9. The Use of Large-Scale Data Sets for the Study of Developmental Science, Pamela Davis-Kean and Justin Jager 10. Telemetrics and Online Data Collection: Collecting Data at a Distance, Joshua Wilt, David M. Condon, and William Revelle 11. Collecting and Analyzing Longitudinal Diary Data, Bernhard Schmitz, Julia Klug, and Silke Hertel 12. Retrospective Methods in Developmental Science, Andrea Follmer Greenhoot 13. Peer Ratings, William M. Bukowski, Antonius H. N. Cillessen, and Ana Maria Velásquez III. Interindividual Longitudinal Analysis 14. Foundational Issues in Investigating Development as Interindividual Variation, Jari-Erik Nurmi 15. Analysis of Experimental and Quasi-Experimental Data: Pinpointing Explanations, Richard Gonzalez, Tianyi Yu, and Brenda Volling 16. Autoregressive and Cross-Lagged Panel Analysis for Longitudinal Data, James P. Selig and Todd D. Little 17. Analyzing Change between Two or More Groups: Analysis of Variance versus Analysis of Covariance, Kamala London and Daniel B. Wright 18. Mediation Models for Developmental Data, Matthew S. Fritz and David P. MacKinnon IV. Intraindividual Longitudinal Analysis 19. Foundational Issues in Intraindividual Longitudinal Analysis, Michael J. Rovine and Lawrence L. Lo 20. Dynamic Factor Analysis and Control of Developmental Processes, Peter C. M. Molenaar and Lawrence L. Lo 21. P-Technique Factor Analysis, Ihno A. Lee and Todd D. Little 22. Hazard, Event History, and Survival Modeling, Margaret K. Keiley, Cassandra Kirkland, Ali Zaremba, and Ashley Anders Jackson V. Combining Interindividual and Intraindividual Longitudinal Analysis 23. Foundational Issues in the Contemporary Modeling of Longitudinal Trajectories, John J. McArdle 24. Growth Curve Modeling from a Structural Equation Modeling Perspective, Kevin J. Grimm and Nilam Ram 25. Growth Curve Modeling from a Multilevel Model Perspective, Joop J. Hox and Jan Boom 26. Nonlinear Growth Modeling, Shelley A. Blozis 27. Group-Based Trajectory Modeling in Developmental Science, Daniel S. Nagin and Candice L. Odgers 28. Longitudinal Mixture Models and the Identification of Archetypes: Action-Adventure, Mystery, Science Fiction, or Romance, Nilam Ram, Kevin J. Grimm, Lisa M. Gatzke-Kopp, and Peter C. M. Molenaar 29. Multilevel Structural Equation Modeling, James A. Bovaird and Leslie H. Shaw VI. Nonindependent Data Analysis 30. Foundational Issues in Nonindependent Data Analysis, William L. Cook 31. Dyadic Data Analyses in a Developmental Context, Robert A. Ackerman, M. Brent Donnellan, Deborah A. Kashy, and Rand D. Conger 32. Applying the Social Relations Model to Developmental Research, Noel A. Card and Russell B. Toomey 33. Analysis of Static Social Networks and Their Developmental Effects, Scott D. Gest and Thomas A. Kindermann 34. Actor-Based Model for Network and Behavior Dynamics, René Veenstra and Christian Steglich VII. Special Topics in Data Analysis 35. Configural Frequency Analysis in Developmental Research, Alexander von Eye, Eun-Young Mun, Richard M. Lerner, Jacqueline V. Lerner, and Edmond P. Bowers 36. Cluster Analysis and Latent Class Clustering Techniques, Christine DiStefano 37. Meta-Analysis in Developmental Science, Marinus H. van IJzendoorn, Marian J. Bakermans-Kranenburg, and Lenneke R. A. Alink 38. Evaluating Gene–Environment Interplay, Mara Brendgen, Frank Vitaro, and Alain Girard 39. Epidemic Models of the Onset of Social Activities, Joseph Lee Rodgers and Andrey Koval 40. Dynamic Systems, Paul van Geert 41. Planned Missing Data Designs for Developmental Research, Stephen A. Mistler and Craig K. Enders