latent growth curve modeling 157 quantitative applications in the social sciences

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Latent Growth Curve Modeling

Author : Kristopher J. Preacher
ISBN : 9781412939553
Genre : Social Science
File Size : 71. 4 MB
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Provides easy-to-follow, didactic examples of several common growth modeling approaches

Latent Class Analysis

Author : Allan L. McCutcheon
ISBN : 0803927525
Genre : Mathematics
File Size : 63. 75 MB
Format : PDF
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Latent class analysis is a powerful tool for analyzing the structure of relationships among categorically scored variables. It enables researchers to explore the suitability of combining two or more categorical variables into typologies or scales. It also provides a method for testing hypotheses regarding the latent structure among categorical variables.

An Introduction To Latent Variable Growth Curve Modeling

Author : Terry E. Duncan
ISBN : 9781135601249
Genre : Business & Economics
File Size : 64. 50 MB
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This book provides a comprehensive introduction to latent variable growth curve modeling (LGM) for analyzing repeated measures. It presents the statistical basis for LGM and its various methodological extensions, including a number of practical examples of its use. It is designed to take advantage of the reader’s familiarity with analysis of variance and structural equation modeling (SEM) in introducing LGM techniques. Sample data, syntax, input and output, are provided for EQS, Amos, LISREL, and Mplus on the book’s CD. Throughout the book, the authors present a variety of LGM techniques that are useful for many different research designs, and numerous figures provide helpful diagrams of the examples. Updated throughout, the second edition features three new chapters—growth modeling with ordered categorical variables, growth mixture modeling, and pooled interrupted time series LGM approaches. Following a new organization, the book now covers the development of the LGM, followed by chapters on multiple-group issues (analyzing growth in multiple populations, accelerated designs, and multi-level longitudinal approaches), and then special topics such as missing data models, LGM power and Monte Carlo estimation, and latent growth interaction models. The model specifications previously included in the appendices are now available on the CD so the reader can more easily adapt the models to their own research. This practical guide is ideal for a wide range of social and behavioral researchers interested in the measurement of change over time, including social, developmental, organizational, educational, consumer, personality and clinical psychologists, sociologists, and quantitative methodologists, as well as for a text on latent variable growth curve modeling or as a supplement for a course on multivariate statistics. A prerequisite of graduate level statistics is recommended.

Democracies And Dictatorships In Latin America

Author : Scott Mainwaring
ISBN : 9780521190015
Genre : Political Science
File Size : 70. 83 MB
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Presents a new theory for why democracies and dictatorships emerge and then survive or collapse via analyses of political regimes in Latin America since 1900.

Mediation Analysis

Author : Dawn Iacobucci
ISBN : 9781412925693
Genre : Mathematics
File Size : 43. 28 MB
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Social science data analysts have long considered the mediation of intermediate variables of primary importance in understanding individuals' social, behavioural and other kinds of outcomes. In this book Dawn Iacobucci uses the method known as structural equation modeling (SEM) in modeling mediation in causal analysis. This approach offers the most flexibility and allows the researcher to deal with mediation in the presence of multiple measures, mediated moderation, and moderated mediation, among other variations on the mediation theme. The wide availability of software implementing SEM gives the reader necessary tools for modeling mediation so that a proper understanding of causal relationship is achieved.

Latent Curve Models

Author : Kenneth A. Bollen
ISBN : 9780471455929
Genre : Mathematics
File Size : 73. 12 MB
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An effective technique for data analysis in the social sciences The recent explosion in longitudinal data in the social sciences highlights the need for this timely publication. Latent Curve Models: A Structural Equation Perspective provides an effective technique to analyze latent curve models (LCMs). This type of data features random intercepts and slopes that permit each case in a sample to have a different trajectory over time. Furthermore, researchers can include variables to predict the parameters governing these trajectories. The authors synthesize a vast amount of research and findings and, at the same time, provide original results. The book analyzes LCMs from the perspective of structural equation models (SEMs) with latent variables. While the authors discuss simple regression-based procedures that are useful in the early stages of LCMs, most of the presentation uses SEMs as a driving tool. This cutting-edge work includes some of the authors' recent work on the autoregressive latent trajectory model, suggests new models for method factors in multiple indicators, discusses repeated latent variable models, and establishes the identification of a variety of LCMs. This text has been thoroughly class-tested and makes extensive use of pedagogical tools to aid readers in mastering and applying LCMs quickly and easily to their own data sets. Key features include: Chapter introductions and summaries that provide a quick overview of highlights Empirical examples provided throughout that allow readers to test their newly found knowledge and discover practical applications Conclusions at the end of each chapter that stress the essential points that readers need to understand for advancement to more sophisticated topics Extensive footnoting that points the way to the primary literature for more information on particular topics With its emphasis on modeling and the use of numerous examples, this is an excellent book for graduate courses in latent trajectory models as well as a supplemental text for courses in structural modeling. This book is an excellent aid and reference for researchers in quantitative social and behavioral sciences who need to analyze longitudinal data.

Causal Analysis With Panel Data

Author : Steven E. Finkel
ISBN : 0803938969
Genre : Medical
File Size : 46. 40 MB
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Panel data — information gathered from the same individuals or units at several different points in time — are commonly used in the social sciences to test theories of individual and social change. This book highlights the developments in this technique in a range of disciplines and analytic traditions.

The Reviewer S Guide To Quantitative Methods In The Social Sciences

Author : Gregory R. Hancock
ISBN : 9781135172992
Genre : Education
File Size : 44. 82 MB
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The Reviewer’s Guide is designed for reviewers of research manuscripts and proposals in the social and behavioral sciences, and beyond. Its uniquely structured chapters address traditional and emerging quantitative methods of data analysis.

A Unified Model For The Analysis Of Individual Latent Trajectories

Author : Chueh-An Hsieh
ISBN : MSU:31293030635555
Genre : Developmental psychology
File Size : 62. 48 MB
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Longitudinal Structural Equation Modeling

Author : Todd D. Little
ISBN : 9781462510276
Genre : Psychology
File Size : 51. 97 MB
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Featuring actual datasets as illustrative examples, this book reveals numerous ways to apply structural equation modeling (SEM) to any repeated-measures study. Initial chapters lay the groundwork for modeling a longitudinal change process, from measurement, design, and specification issues to model evaluation and interpretation. Covering both big-picture ideas and technical "how-to-do-it" details, the author deftly walks through when and how to use longitudinal confirmatory factor analysis, longitudinal panel models (including the multiple-group case), multilevel models, growth curve models, and complex factor models, as well as models for mediation and moderation. User-friendly features include equation boxes that clearly explain the elements in every equation, end-of-chapter glossaries, and annotated suggestions for further reading. The companion website (www.guilford.com/little-materials) provides datasets for all of the examples--which include studies of bullying, adolescent students' emotions, and healthy aging--with syntax and output from LISREL, Mplus, and R (lavaan).

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