{"product_id":"growth-modeling-9781462526062","title":"Growth Modeling","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eGrowth models are among the core methods for analyzing how and when people change. Discussing both structural equation and multilevel modeling approaches, this book leads readers step by step through applying each model to longitudinal data to answer particular research questions. It demonstrates cutting-edge ways to describe linear and nonlinear change patterns, examine within-person and between-person differences in change, study change in latent variables, identify leading and lagging indicators of change, evaluate co-occurring patterns of change across multiple variables, and more. User-friendly features include real data examples, code (for Mplus or NLMIXED in SAS, and OpenMx or nlme in R), discussion of the output, and interpretation of each model's results.\u003cbr\u003e\u003cbr\u003e User-Friendly Features\u003cbr\u003e *Real, worked-through longitudinal data examples serving as illustrations in each chapter.\u003cbr\u003e *Script boxes that provide code for fitting the models to example data and facilitate applic\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\"This is by far the most comprehensive, up-to-date, and ready-to-use book on growth modeling that I have ever seen. The authors have proven records in effectively teaching classes and workshops on longitudinal data analysis. This is a 'must have' for anyone who wants to develop or apply growth models. The SAS, Mplus, and OpenMx example scripts and instructions are long-needed complements to those programs' respective manuals. Coverage includes the most recent developments in growth modeling, and each chapter essentially can stand by itself, providing enough information for researchers to apply the respective models in their studies to answer more complex and interesting empirical questions. The book can be used in a range of classes either as a main text or a supplement. I will definitely recommend it to students in my Structural Equation Modeling class when I teach structural growth curve modeling.\"--Zhiyong Johnny Zhang, PhD, Department of Psychology, University of Notre Dame\u003cbr\u003e\u003cbr\u003e \"The implementation details are superb and the level of technical detail quite stunning. It will be so helpful for longitudinal researchers to have this compendium of growth models, complete with sample code from both SEM and multilevel modeling frameworks. It is wonderful to see the item response theory and SEM frameworks so nicely integrated. The authors have hit the trifecta--pulling together multilevel modeling, SEM, and item response theory. There is truly no other book on the market that covers latent growth modeling so completely and comprehensively.\"--D. Betsy McCoach, PhD, Measurement, Evaluation, and Assessment Program, Neag School of Education, University of Connecticut\u003cbr\u003e\u003cbr\u003e \"This is the most thorough work on this subject that I know of; the coverage of nonlinear models is among the best I have seen. The book is written at a level suitable for an advanced graduate student learning this material or an applied researcher seeking a reference on the subject. It introduces the basics, discusses the relevant model theory\/specification, and presents programming code for several packages. The authors do an exceptional job of explaining the computer code and providing insight into convergence issues and how to remedy them. It is good to have this all in one place (along with the respective output) for comparative purposes.\"--Daniel A. Powers, PhD, Department of Sociology, University of Texas at Austin\u003cbr\u003e\u003cbr\u003e \"This well-written book starts with clear statements about what research questions can be answered using growth models. Usefully, the authors include both multilevel modeling and SEM approaches, and analyze the example data within each framework using one proprietary program and one freely available R package. Viewing the detailed code and the results of each analysis gives the reader a chance to understand the strengths and weaknesses of each approach. Later chapters address such developments as nonlinear growth models and growth models for noncontinuous outcomes. Code for each variation is given, which expand the researcher's capacity to fit these complex models.\"--Yasuo Miyazaki, PhD, Associate Professor of Educational Research and Evaluation Program, Virginia Tech\u003cbr\u003e\u003cbr\u003e \"The importance that researchers and practitioners are placing on longitudinal designs and analyses signals a prominent shift toward methods that enable a better understanding of the developmental processes thought to underlie many human traits and behaviors. This book provides the essential background on latent growth models and covers several interesting methodological extensions, including models for nonlinear change, growth mixture models, and longitudinal models for assessing change in latent variables. Practical examples are woven throughout the text, accompanied by extensive annotated code in SAS, Mplus, and R, which makes both basic and more complex models accessible. This is a wonderful resource for anyone serious about longitudinal data analysis.\"--Jeffrey R. Harring, PhD, Department of Human Development and Quantitative Methodology, University of Maryland \u003cbr\u003e\u003cbr\u003e \"I highly recommend this book. It is a tour de force in model building with latent growth curves. The authors' use of three programming languages (Mplus, SAS, and R) is great, and they work with computer programs in an unusually careful way. The book will be of value to anyone dealing with longitudinal data.\"--John J. McArdle, PhD, Department of Psychology, University of Southern California -An accessible resource that provides a thorough introduction to frequently used longitudinal models….An invaluable resource for students and scholars….This book would be excellent reading material for students in various disciplines, such as psychology and education, that provide either introductory or advanced longitudinal graduate courses.--Psychometrika, 03\/01\/2019\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eI. Introduction and Organization\u003cbr\u003e 1. Overview, Goals of Longitudinal Research, and Historical Developments\u003cbr\u003e Overview\u003cbr\u003e Five Rationales for Longitudinal Research\u003cbr\u003e Historical Development of Growth Models\u003cbr\u003e Modeling Frameworks and Programs\u003cbr\u003e 2. Practical Preliminaries: Things to Do before Fitting Growth Models\u003cbr\u003e Data Structures\u003cbr\u003e Longitudinal Plots\u003cbr\u003e Data Screening\u003cbr\u003e Longitudinal Measurement\u003cbr\u003e Time Metrics\u003cbr\u003e Change Hypotheses\u003cbr\u003e Incomplete Data\u003cbr\u003e Moving Forward\u003cbr\u003e II. The Linear Growth Model and Its Extensions\u003cbr\u003e 3. Linear Growth Models\u003cbr\u003e Multilevel Modeling Framework\u003cbr\u003e Multilevel Modeling Implementation\u003cbr\u003e Structural Equation Modeling Framework\u003cbr\u003e Structural Equation Modeling Implementation\u003cbr\u003e Important Considerations\u003cbr\u003e Moving Forward\u003cbr\u003e 4. Continuous Time Metrics\u003cbr\u003e Multilevel Modeling Framework\u003cbr\u003e Multilevel Modeling Implementation\u003cbr\u003e Structural Equation Modeling Framework\u003cbr\u003e Structural Equation Modeling Implementation\u003cbr\u003e Important Considerations\u003cbr\u003e Moving Forward\u003cbr\u003e 5. Linear Growth Models with Time-Invariant Covariates\u003cbr\u003e Multilevel Model Framework\u003cbr\u003e Multilevel Modeling Implementation\u003cbr\u003e Structural Equation Modeling Framework\u003cbr\u003e Structural Equation Modeling Implementation\u003cbr\u003e Important Considerations\u003cbr\u003e Moving Forward\u003cbr\u003e 6. Multiple-Group Growth Modeling\u003cbr\u003e Multilevel Modeling Framework\u003cbr\u003e Multilevel Modeling Implementation\u003cbr\u003e Structural Equation Modeling Framework\u003cbr\u003e Structural Equation Modeling Implementation\u003cbr\u003e Important Considerations\u003cbr\u003e Moving Forward\u003cbr\u003e 7. Growth Mixture Modeling\u003cbr\u003e Multilevel Modeling Framework\u003cbr\u003e Multilevel Modeling Implementation\u003cbr\u003e Structural Equation Modeling Framework\u003cbr\u003e Structural Equation Modeling Implementation\u003cbr\u003e Model Fit, Model Comparison, and Class Enumeration\u003cbr\u003e Important Considerations\u003cbr\u003e Moving Forward\u003cbr\u003e 8. Multivariate Growth Models and Dynamic Predictors\u003cbr\u003e Multilevel Modeling Framework\u003cbr\u003e Multilevel Modeling Implementation\u003cbr\u003e Structural Equation Modeling Framework\u003cbr\u003e Structural Equation Modeling Implementation\u003cbr\u003e Important Considerations\u003cbr\u003e Moving Forward\u003cbr\u003e III. Nonlinearity in Growth Modeling\u003cbr\u003e 9. Introduction to Nonlinearity\u003cbr\u003e Organization for Nonlinear Change Models\u003cbr\u003e Moving Forward\u003cbr\u003e 10. Growth Models with Nonlinearity in Time\u003cbr\u003e Multilevel Modeling Framework\u003cbr\u003e Multilevel Modeling Implementation\u003cbr\u003e Structural Equation Modeling Framework\u003cbr\u003e Structural Equation Modeling Implementation\u003cbr\u003e Important Considerations\u003cbr\u003e Moving Forward\u003cbr\u003e 11. Growth Models with Nonlinearity in Parameters\u003cbr\u003e Multilevel Modeling Framework\u003cbr\u003e Multilevel Modeling Implementation\u003cbr\u003e Structural Equation Modeling Framework\u003cbr\u003e Structural Equation Modeling Implementation\u003cbr\u003e Important Considerations\u003cbr\u003e Moving Forward\u003cbr\u003e 12. Growth Models with Nonlinearity in Random Coefficients\u003cbr\u003e Multilevel Modeling Framework\u003cbr\u003e Multilevel Modeling Implementation\u003cbr\u003e Structural Equation Modeling Framework\u003cbr\u003e Structural Equation Modeling Implementation\u003cbr\u003e Important Considerations\u003cbr\u003e Moving Forward\u003cbr\u003e IV. Modeling Change with Latent Entities\u003cbr\u003e 13. Modeling Change with Ordinal Outcomes\u003cbr\u003e Dichotomous Outcomes\u003cbr\u003e Polytomous Outcomes\u003cbr\u003e Illustration\u003cbr\u003e Multilevel Modeling Implementation\u003cbr\u003e Structural Equation Modeling Implementation\u003cbr\u003e Important Considerations\u003cbr\u003e Moving Forward\u003cbr\u003e 14. Modeling Change with Latent Variables Measured by Continuous Indicators\u003cbr\u003e Common-Factor Model\u003cbr\u003e Factorial Invariance over Time\u003cbr\u003e Second-Order Growth Model\u003cbr\u003e Illustration\u003cbr\u003e Structural Equation Modeling Implementation\u003cbr\u003e Important Considerations\u003cbr\u003e Moving Forward\u003cbr\u003e 15. Modeling Change with Latent Variables Measured by Ordinal Indicators\u003cbr\u003e Item Response Modeling\u003cbr\u003e Second-Order Growth Model\u003cbr\u003e Illustration\u003cbr\u003e Important Considerations\u003cbr\u003e Moving Forward\u003cbr\u003e V. Latent Change Scores as a Framework for Studying Change\u003cbr\u003e 16. Introduction to Latent Change Score Modeling\u003cbr\u003e General Model Specification\u003cbr\u003e Models of Change\u003cbr\u003e Illustration\u003cbr\u003e Structural Equation Modeling Implementation\u003cbr\u003e Important Considerations\u003cbr\u003e Moving Forward\u003cbr\u003e 17. Multivariate Latent Change Score Models\u003cbr\u003e Autoregressive Cross-Lag Model\u003cbr\u003e Multivariate Growth Model\u003cbr\u003e Multivariate Latent Change Score Model\u003cbr\u003e Illustration\u003cbr\u003e Structural Equation Modeling Implementation\u003cbr\u003e Important Considerations\u003cbr\u003e Moving Forward\u003cbr\u003e 18. Rate-of-Change Estimates in Nonlinear Growth Models\u003cbr\u003e Growth Rate Models\u003cbr\u003e Latent Change Score Models\u003cbr\u003e Illustration\u003cbr\u003e Multilevel Modeling Implementation\u003cbr\u003e Structural Equation Modeling Implementation\u003cbr\u003e Important Considerations\u003cbr\u003e Appendix A. A Brief Introduction to Multilevel Modeling\u003cbr\u003e Illustrative Example\u003cbr\u003e Multilevel Modeling and Longitudinal Data\u003cbr\u003e Appendix B. A Brief Introduction to Structural Equation Modeling\u003cbr\u003e Illustrative Example\u003cbr\u003e Structural Equation Modeling and Longitudinal Data\u003cbr\u003e References\u003cbr\u003e Author Index\u003cbr\u003e Subject Index\u003cbr\u003e About the Authors\u003c\/p\u003e","brand":"Guilford Publications","offers":[{"title":"Default Title","offer_id":49371923349847,"sku":"9781462526062","price":67.44,"currency_code":"GBP","in_stock":true}],"url":"https:\/\/bookcurl.com\/products\/growth-modeling-9781462526062","provider":"Book Curl","version":"1.0","type":"link"}