Handbook of Research Methods in Developmental Science
Description
Presents cutting-edge research methods in developmental science
The Handbook of Research Methods in Developmental Science delivers a fully revised and expanded exploration of the latest methodologies in human development research. Twenty-four entirely new chapters by renowned experts introduce innovative approaches that reflect the dynamic evolution of developmental science methodologies. Part of the Blackwell Handbooks of Research Methods in Psychology series, this authoritative resource is indispensable for those seeking to apply state-of-the-art methods to the study of human development.
The second edition of the Handbook builds upon the strengths of its predecessor while incorporating significant updates to address emerging research challenges. It offers a comprehensive review of traditional and contemporary developmental research designs, including cross-sectional, longitudinal, and quasi-experimental methods, as well as advanced topics such as the Multiphasic Optimization Strategy (MOST) framework, time-varying effect modeling, and integrative data analysis. Additionally, the authors present fresh insights into causal inference, observational methods, and intervention research, providing a more nuanced understanding of how developmental scientists can study change over time.
Capturing the latest theoretical and technological advancements in the discipline, the Handbook of Research Methods in Developmental Science:
- Features a multidisciplinary approach, integrating perspectives from psychology, human development, and family science
- Addresses challenges in developmental intervention research, including implementation science and adaptive intervention design
- Offers practical guidance on participant recruitment, panel maintenance, and best practices for obtaining reliable developmental data
- Includes real-world examples and case studies demonstrating the application of various research methods
The Handbook of Research Methods in Developmental Science, Second Edition, is an essential resource for graduate students, researchers, and professionals in developmental science, psychology, and human development. It is particularly relevant for courses in research methods, developmental psychology, and intervention science within psychology, education, and social sciences degree programs.
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Persons
Douglas M. Teti, PhD, is a Distinguished Professor in the Department of Human Development and Family Science at The Pennsylvania State University. A leading expert in developmental science, his research focuses on family processes, parenting, and infant development.
Hobart Harrington Cleveland III, JD, PhD, is a Professor in the Department of Human Development and Family Science at The Pennsylvania State University. His research explores adolescent development, peer relationships, and substance use prevention.
Kelly L. Rulison, PhD, is a Senior Research Scientist at Prevention Strategies. A former Associate Professor at The Pennsylvania State University, Dr. Rulison's work focuses on designing and evaluating developmental interventions to improve social and behavioral outcomes.
Content
Author Bios viii
Preface xxiv
Part I Developmental Designs, Sampling, and Causal Inference 1
1 Cross- Sectional, Longitudinal, and Retrospective Designs: General Utility and Threats to Validity 3
Ekjyot K. Saini and Douglas M. Teti
2 Experimental Design in Developmental Science 31
Robert Hepach
3 Strengthening Causal Inference Using Sibling Designs 57
Gabriel L. Schlomer, Olivia C. Robertson, and Kristine Marceau Copyrighted Material
4 Quasi- Experimental Designs for Causal Inference About Intervention Effects: Addressing Threats to Validity from a Graphical Models Perspective 79
Patrick Sheehan, Muwon Kwon, and Peter M. Steiner
5 Measurement Burst Designs in Developmental Science 110
Daisy V. Zavala, Giselle A. Ferguson, Giancarlo Pasquini, and Stacey B. Scott
6 Obtaining and Keeping Your Sample: Participant Recruitment and Panel Maintenance 129
Carina Cornesse and Bella Struminskaya
7 On Sampling and Measurement: A Case Study of the Association Between Loneliness and Cognitive Function in the Survey of Health Aging and Retirement in Europe 146
Ashton M. Verdery and Mara Getz Sheftel
Part II Construct Measurement in Developmental and Family Science 181
8 Conceptualizing and Measuring the Family Context 183
Gregory M. Fosco and Devin Malloy McCauley
9 Direct and Indirect Observational Methods in Developmental and Family Science 200
Rena L. Repetti
10 Assessing Parenting in Context: Naturalistic Assessment, Domain Specificity, and Early Development 220
Douglas M. Teti
11 Maximizing Cultural Validity in the Study of Child Development 250
Suzanne Gaskins
12 Introduction to Qualitative Methods in Developmental Science 276
Debbie Kim and Rachel Carly Feldman
Part III Advances in Developmental Intervention 301
13 The Multiphase Optimization Strategy (MOST): A Framework to Develop More Effective, Affordable, Scalable, and Efficient Interventions 303
Kelly L. Rulison
14 The Sequential Multiple Assignment Randomized Trial (SMART) Design 329
Xiaoxi Yan, Yifan Cui, and Bibhas Chakraborty
Contents vii
15 Adaptive Intervention Designs for Studies of Human Development 349
Timothy R. Brick
16 Economic Evaluation of Developmental Interventions: Issues and Best Practices 370
Lawrie Green Daniel (Max) Crowley
17 Bringing Interventions to Scale: Research Methods for Dissemination and Implementation Science 389
Gitanjali Shrestha and Brittany Cooper
Part IV Data Analysis and Methods in Developmental Science 411
18 It's All Regression: Fundamentals of Developmental Data Analysis 413
Michael J. Rovine, Emily M. Weiss, and Paul A. McDermott
19 Modern Causal Mediation and Longitudinal Models for Developmental Data 453
Matthew J. Valente, Judith J. M. Rijnhart, and David P. MacKinnon
20 A Rosetta Stone for Modeling Change: Connections among Multilevel Models, Structural Equation Models, and Multilevel Structural Equation Models 483
Lesa Hoffman
21 Integrative Data Analysis in Developmental Science: A Primer 516
Veronica T. Cole, Conor H. Lacey, and Lydia F. Bierce
22 Propensity Score Methods in Quasi- Experimental Research 544
Donna L. Coffman
23 Applications of Social Network Analysis in Developmental Science 560
Andrea Vest Ettekal and Jimi Adams
24 Time- Varying Effect Modeling to Address Novel Questions in Developmental Research 583
Stephanie T. Lanza and Anna K. Hochgraf
Author Index 612
Subject Index 643
