This volume reviews the challenges and alternative approaches to modeling how individuals change across time and provides methodologies and data analytic strategies for behavioral and social science researchers. This accessible guide provides concrete, clear examples of how contextual factors can be included in most research studies. Each chapter can be understood independently, allowing readers to first focus on areas most relevant to their work. The opening chapter demonstrates the various ways contextual factors are represented—as covariates, predictors, outcomes, moderators, mediators, or mediated effects. Succeeding chapters review "best practice" techniques for treating missing data, making model comparisons, and scaling across developmental age ranges. Other chapters focus on specific statistical techniques such as multilevel modeling and multiple-group and multilevel SEM, and how to incorporate tests of mediation, moderation, and moderated mediation. Critical measurement and theoretical issues are discussed, particularly how age can be represented and the ways in which context can be conceptualized. The final chapter provides a compelling call to include contextual factors in theorizing and research. This book will appeal to researchers and advanced students conducting developmental, social, clinical, or educational research, as well as those in related areas such as psychology and linguistics.
Author(s): Todd D. Little, James A. Bovaird, Noel A. Card
Edition: 1
Year: 2007
Language: English
Pages: 392
Front cover......Page 1
Contents......Page 6
Preface......Page 8
CHAPTER ONE. Modeling Ecological and Contextual Effects in Longitudinal Studies of Human Development......Page 10
CHAPTER TWO. Statistical Analysis With Incomplete Data: A Developmental Perspective......Page 22
CHAPTER THREE. Alternatives to Traditional Model Comparison Strategies for Covariance Structures Models......Page 42
CHAPTER FOUR. Impact of Measurement Scale in Modeling Development Processes and Ecological Factors......Page 72
CHAPTER FIVE. The Incorporation of Categorical Measurement Models in the Analysis of Individual Growth......Page 98
CHAPTER SIX. Representing Contextual Effects in Multiple-Growth MACS Models......Page 130
CHAPTER SEVEN. Multilevel Structural Equation Models for Contextual Factors......Page 158
CHAPTER EIGHT. Mixed-Effects Regression Models With Heterogeneous Variance: Analyzing Ecological Momentary Assessment (EMA) Data of Smoking......Page 192
CHAPTER NINE. Structural Equation Modeling of Mediation and Moderation With Contextual Factors......Page 216
CHAPTER TEN. Moderating Effects of a Risk Factor: Modeling Longitudinal Moderated Mediation in the Development of Adolescent Heavy Drinking......Page 240
CHAPTER ELEVEN. Modeling Compelx Interactions: Person-Centered and Variable-Centered Approaches......Page 264
CHAPTER TWELVE. Accounting for Statistical Dependency in Longitudinal Data on Dyads......Page 294
CHAPTER THIRTEEN. Coupled Dynamics and Mutually Adaptive Context......Page 308
CHAPTER FOURTEEN. Modeling Intraindividual and Intracontextual Change: Rendering Developmental Contextualism Operational......Page 334
CHAPTER FIFTEEN. The Shape of Things to Come: Diagnosing Social Contagion From Adolescent Smoking and Drinking Curves......Page 352
CHAPTER SIXTEEN. A Dynamic Structural Analysis of the Impacts of Context on Shifts in Lifespan Cognitive Development......Page 372
CHAPTER SEVENTEEN. Intrauterine Environment Affects Infant and Child Intellectual Outcomes: Environment as Direct Effect......Page 396
CHAPTER EIGHTEEN. Conceptualizing and Measuring the Context Within Person Context Models of Human Development: Implications for Theory, Research and Application......Page 446
Author Index......Page 466
Subject Index......Page 478
Back cover......Page 482
