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Growth 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...
This volume presents a collection of chapters focused on the study of multivariate change. As people develop and change, multivariate measurement of that change and analysis of those measures can illuminate the regularities in the trajectories of individual development, as well as time-dependent changes in population averages. As longitudinal data have recently become much more prevalent in psychology and the social sciences, models of change have become increasingly important. This collection focuses on methodological, statistical, and modeling aspects of multivariate change and applications of longitudinal models to the study of psychological processes. The volume is divided into three major sections: Extension of latent change models, Measurement and testing issues in longitudinal modeling, and Novel applications of multivariate longitudinal methodology. It is intended for advanced students and researchers interested in learning about state-of-the-art techniques for longitudinal data analysis, as well as understanding the history and development of such techniques.
"Over the past 20 years, there has been an incredible change in the size, structure, and types of data collected in the social and behavioral sciences. Thus, social and behavioral researchers have increasingly been asking the question: "What do I do with all of this data?" The goal of this book is to help answer that question. It is our viewpoint that in social and behavioral research, to answer the question "What do I do with all of this data?", one needs to know the latest advances in the algorithms and think deeply about the interplay of statistical algorithms, data, and theory. An important distinction between this book and most other books in the area of machine learning is our focus on theory"--
Exploring the challenges and risks of social science fieldwork, this book shares best practice for conducting research in hostile environments and pragmatic advice to help you make good decisions. Drawing on the authors’ experiences in regions of conflict and grounded in real-world examples, the book: · Provides practical guidance on important considerations like choosing a research question in sensitive contexts · Gives advice on data and digital security to help you minimize fieldwork risk in a contemporary research environment · Offers tools and templates you can use to develop a tailored security framework Building your understanding of the challenges of on-the-ground research, this book empowers you to meet the challenges of your research landscape head on.
Since Charles Spearman published his seminal paper on factor analysis in 1904 and Karl Joresk ̈ og replaced the observed variables in an econometric structural equation model by latent factors in 1970, causal modelling by means of latent variables has become the standard in the social and behavioural sciences. Indeed, the central va- ables that social and behavioural theories deal with, can hardly ever be identi?ed as observed variables. Statistical modelling has to take account of measurement - rors and invalidities in the observed variables and so address the underlying latent variables. Moreover, during the past decades it has been widely agreed on that serious causal modelling should be based on longitudinal data. It is especially in the ?eld of longitudinal research and analysis, including panel research, that progress has been made in recent years. Many comprehensive panel data sets as, for example, on human development and voting behaviour have become available for analysis. The number of publications based on longitudinal data has increased immensely. Papers with causal claims based on cross-sectional data only experience rejection just for that reason.
This indispensible sourcebook covers conceptual and practical issues in research design in the field of social and personality psychology. Key experts address specific methods and areas of research, contributing to a comprehensive overview of contemporary practice. This updated and expanded second edition offers current commentary on social and personality psychology, reflecting the rapid development of this dynamic area of research over the past decade. With the help of this up-to-date text, both seasoned and beginning social psychologists will be able to explore the various tools and methods available to them in their research as they craft experiments and imagine new methodological possibilities.
The seminal reference for the latest research in developmental psychopathology Developmental Psychopathology is a four-volume compendium of the most complete and current research on every aspect of the field. Volume One: Theory and Method focuses on the theoretical and empirical work that has contributed to dramatic advancements in understanding of child and adult development, including findings in the areas of genetics and neurobiology, as well as social and contextual factors. Now in its third edition, this comprehensive reference has been fully updated to reflect the current state of the field and its increasingly multilevel and interdisciplinary nature and the increasing importance of tr...
"In the novel Bel Canto, the Vice-President of a small Latin American country and about 50 others are being held hostage by terrorists. They have been held in the Vice-President's mansion for months and they fear they will not survive. Vice President Ruben Iglesias, who thought he would not live to feel once again the sensation of grass beneath his feet, stepped off the shale stone walkway and sank into the luxury of his own yard. He had stared at it every day from the living-room window but now that he was actually there it seemed like a new world. Had he ever walked around his own lawn in the evening? Had he made a mental note of the trees, the miraculous flowering bushes that grew up around the wall? What were they called? He dropped his face into the nest of deep purple blossoms and inhaled. Dear God, if he were to get out of this alive he would be attentive to his plants. (Patchett 2001: 281)"--
"This book provides young scientists with tools to assist them in the practical aspects of theory construction. We take an informal journey through the cognitive heuristics, tricks of the trade, and ways of thinking that we have found to be useful in developing theories-essentially, conceptualizations-that can advance knowledge in the social sciences. This book is intended to provide the instructor with a useful source for helping students come up with ideas for research and for fine-tuning the resultant theories that emerge from such thinking. An objective of this book is to move toward a needed balance in the emphases given to theory construction and theory testing"--
This book has been replaced by Longitudinal Structural Equation Modeling, Second Edition, ISBN 978-1-4625-5314-3.