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…mehr
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.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Todd D. Little is Director of the Research Design Unit and the Quantitative Psychology Doctoral training Program and a Professor of Psychology at the University of Kansas. He received his Ph.D. in developmental and quantitative psychology at the University of California - Riverside. Dr. Little has extensive experience in the use of longitudinal research methods, and he has edited several LEA books on the subject. James A. Bovaird is an Assistant Professor in Educational Psychology at the University of Nebraska - Lincoln. He received his Ph.D. in quantitative psychology at the University of Kansas. His quantitative interests are in the application of latent variable methodologies to novel substantive areas and the evaluation of these methodologies in situations of limited inference. Noel A. Card is an Assistant Professor in the Division of Family Studies and Human Development at the University of Arizona. He received his Ph.D. in clinical psychology from St. John's University. His quantitative interests are structural equation modeling, longitudinal design and analysis, meta-analysis, and analyzing interdependent data.
Inhaltsangabe
Contents: Preface. N.A. Card T.D. Little J.A. Bovaird Modeling Ecological and Contextual Effects in Longitudinal Studies of Human Development. S.M. Hofer L. Hoffman Statistical Analysis With Incomplete Data: A Developmental Perspective. K.J. Preacher L. Cai R.C. MacCullum Alternatives to Traditional Model Comparison Strategies for Covariance Structure Models. S.E. Embretson Impact of Measurement Scale in Modeling Developmental Processes and Ecological Factors. P.J. Curran M.C. Edwards R.J. Wirth A.M. Hussong L. Chassin The Incorporation of Categorical Measurement Models in the Analysis of Individual Growth. T.D. Little N.A. Card D.W. Slegers E.C. Ledford Representing Contextual Effects in Multiple-Group MACS Models. J.A. Bovaird Multilevel Structural Equation Models for Contextual Factors. D. Hedeker R.J. Mermelstein Mixed-Effects Regression Models With Heterogeneous Variance: Analyzing Ecological Momentary Assessment (EMA) Data of Smoking. T.D. Little N.A. Card J.A. Bovaird K.J. Preacher C.S. Crandel Structural Equation Modeling of Mediation and Moderation With Contextual Factors. D.B. Flora S.T. Khoo L. Chassin Moderating Effects of a Risk Factor: Modeling Longitudinal Moderated Mediation in the Development of Adolescent Heavy Drinking. D.J. Bauer M.J. Shanahan Modeling Complex Interactions: Person-Centered and Variable-Centered Approaches. N. Bolger P.E. Shrout Accounting for Statistical Dependency in Longitudinal Data on Dyads. S.M. Boker J-P. Laurenceau Coupled Dynamics and Mutually Adaptive Context. N. Ram J.R. Nesselroade Modeling Intraindividual and Intracontextual Change: Rendering Developmental Contextualism Operational. J.L. Rodgers The Shape of Things to Come: Using Developmental Curves From Adolescent Smoking and Drinking Reports to Diagnose the Type of Social Process that Generated the Curves. K.J. Grimm J.J. McArdle A Dynamic Structural Analysis of the Impacts of Context on Shifts in Lifespan Development. K.F. Widaman Intrauterine Environment Affects Infant and Child Intellectual Outcomes: Environment as Direct Effect. H. Jelicic C. Theokas E. Phelps R.M. Lerner Conceptualizing and Measuring the Context Within Person Context Models of Human Development: Implications for Theory Research and Application.
Contents: Preface. N.A. Card T.D. Little J.A. Bovaird Modeling Ecological and Contextual Effects in Longitudinal Studies of Human Development. S.M. Hofer L. Hoffman Statistical Analysis With Incomplete Data: A Developmental Perspective. K.J. Preacher L. Cai R.C. MacCullum Alternatives to Traditional Model Comparison Strategies for Covariance Structure Models. S.E. Embretson Impact of Measurement Scale in Modeling Developmental Processes and Ecological Factors. P.J. Curran M.C. Edwards R.J. Wirth A.M. Hussong L. Chassin The Incorporation of Categorical Measurement Models in the Analysis of Individual Growth. T.D. Little N.A. Card D.W. Slegers E.C. Ledford Representing Contextual Effects in Multiple-Group MACS Models. J.A. Bovaird Multilevel Structural Equation Models for Contextual Factors. D. Hedeker R.J. Mermelstein Mixed-Effects Regression Models With Heterogeneous Variance: Analyzing Ecological Momentary Assessment (EMA) Data of Smoking. T.D. Little N.A. Card J.A. Bovaird K.J. Preacher C.S. Crandel Structural Equation Modeling of Mediation and Moderation With Contextual Factors. D.B. Flora S.T. Khoo L. Chassin Moderating Effects of a Risk Factor: Modeling Longitudinal Moderated Mediation in the Development of Adolescent Heavy Drinking. D.J. Bauer M.J. Shanahan Modeling Complex Interactions: Person-Centered and Variable-Centered Approaches. N. Bolger P.E. Shrout Accounting for Statistical Dependency in Longitudinal Data on Dyads. S.M. Boker J-P. Laurenceau Coupled Dynamics and Mutually Adaptive Context. N. Ram J.R. Nesselroade Modeling Intraindividual and Intracontextual Change: Rendering Developmental Contextualism Operational. J.L. Rodgers The Shape of Things to Come: Using Developmental Curves From Adolescent Smoking and Drinking Reports to Diagnose the Type of Social Process that Generated the Curves. K.J. Grimm J.J. McArdle A Dynamic Structural Analysis of the Impacts of Context on Shifts in Lifespan Development. K.F. Widaman Intrauterine Environment Affects Infant and Child Intellectual Outcomes: Environment as Direct Effect. H. Jelicic C. Theokas E. Phelps R.M. Lerner Conceptualizing and Measuring the Context Within Person Context Models of Human Development: Implications for Theory Research and Application.
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