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 : 36. 63 MB
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Provides easy-to-follow, didactic examples of several common growth modeling approaches

The Reviewer S Guide To Quantitative Methods In The Social Sciences

Author : Gregory R. Hancock
ISBN : 9781135172992
Genre : Education
File Size : 45. 27 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 : 38. 18 MB
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Quantitative Narrative Analysis

Author : Roberto Franzosi
ISBN : 9781412925259
Genre : Language Arts & Disciplines
File Size : 81. 65 MB
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Researchers and students in the social sciences.

Dependent Data In Social Sciences Research

Author : Mark Stemmler
ISBN : 9783319205854
Genre : Social Science
File Size : 24. 62 MB
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This volume presents contributions on handling data in which the postulate of independence in the data matrix is violated. When this postulate is violated and when the methods assuming independence are still applied, the estimated parameters are likely to be biased, and statistical decisions are very likely to be incorrect. Problems associated with dependence in data have been known for a long time, and led to the development of tailored methods for the analysis of dependent data in various areas of statistical analysis. These methods include, for example, methods for the analysis of longitudinal data, corrections for dependency, and corrections for degrees of freedom. This volume contains the following five sections: growth curve modeling, directional dependence, dyadic data modeling, item response modeling (IRT), and other methods for the analysis of dependent data (e.g., approaches for modeling cross-section dependence, multidimensional scaling techniques, and mixed models). Researchers and graduate students in the social and behavioral sciences, education, econometrics, and medicine will find this up-to-date overview of modern statistical approaches for dealing with problems related to dependent data particularly useful.

Research Methods In Occupational Health Psychology

Author : Robert R. Sinclair
ISBN : 9781136212390
Genre : Psychology
File Size : 50. 12 MB
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Research Methods in Occupational Health Psychology: Measurement, Design, and Data Analysis provides a state-of-the-art review of current issues and best practices in the science of Occupational Health Psychology. Occupational Health Psychology (OHP) is a multidisciplinary and rapidly growing area of research and it is difficult or impossible for researchers to keep up with developments in all of the fields where scholars conduct OHP science. This book will help OHP scholars improve their own research by translating recent innovations in methodology into sets of concrete recommendations that will help scholars improve their own research as well as their training of future researchers.

Longitudinal Structural Equation Modeling

Author : Todd D. Little
ISBN : 9781462510276
Genre : Psychology
File Size : 45. 96 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).

Missing Data

Author : Paul D. Allison
ISBN : 9781452207902
Genre : Social Science
File Size : 77. 1 MB
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Using numerous examples and practical tips, this book offers a nontechnical explanation of the standard methods for missing data (such as listwise or casewise deletion) as well as two newer (and, better) methods, maximum likelihood and multiple imputation. Anyone who has relied on ad-hoc methods that are statistically inefficient or biased will find this book a welcome and accessible solution to their problems with handling missing data.

The Sage Handbook Of Quantitative Methodology For The Social Sciences

Author : David Kaplan
ISBN : 9781483365879
Genre : Social Science
File Size : 70. 69 MB
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The SAGE Handbook of Quantitative Methodology for the Social Sciences is the definitive reference for teachers, students, and researchers of quantitative methods in the social sciences, as it provides a comprehensive overview of the major techniques used in the field. The contributors, top methodologists and researchers, have written about their areas of expertise in ways that convey the utility of their respective techniques, but, where appropriate, they also offer a fair critique of these techniques. Relevance to real-world problems in the social sciences is an essential ingredient of each chapter and makes this an invaluable resource.

The Association Graph And The Multigraph For Loglinear Models

Author : Harry J. Khamis
ISBN : 9781452238951
Genre : Mathematics
File Size : 65. 30 MB
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The Association Graph and the Multigraph for Loglinear Models will help students, particularly those studying the analysis of categorical data, to develop the ability to evaluate and unravel even the most complex loglinear models without heavy calculations or statistical software. This supplemental text reviews loglinear models, explains the association graph, and introduces the multigraph to students who may have little prior experience of graphical techniques, but have some familiarity with categorical variable modeling. The author presents logical step-by-step techniques from the point of view of the practitioner, focusing on how the technique is applied to contingency table data and how the results are interpreted.

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