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Data Analysis With Mplus

Author: Christian Geiser
Publisher: Guilford Press
ISBN: 1462502458
Size: 57.84 MB
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A practical introduction to using Mplus for the analysis of multivariate data, this volume provides step-by-step guidance, complete with real data examples, numerous screen shots, and output excerpts. The author shows how to prepare a data set for import in Mplus using SPSS. He explains how to specify different types of models in Mplus syntax and address typical caveats--for example, assessing measurement invariance in longitudinal SEMs. Coverage includes path and factor analytic models as well as mediational, longitudinal, multilevel, and latent class models. Specific programming tips and solution strategies are presented in boxes in each chapter. The companion website ( features data sets, annotated syntax files, and output for all of the examples. Of special utility to instructors and students, many of the examples can be run with the free demo version of Mplus.

The Sage Handbook Of Quantitative Methodology For The Social Sciences

Author: David Kaplan
Publisher: SAGE Publications
ISBN: 1483365875
Size: 15.24 MB
Format: PDF, Mobi
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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.

Advanced Multivariate Data Analysis With Mplus

Author: Christian Geiser
Publisher: Springer VS
ISBN: 9783531166049
Size: 30.46 MB
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Der zweite Band von "Datenanalyse mit Mplus" wendet sich an fortgeschrittene Anwender, die über solides statistisches Hintergrundwissen und erste Mplus-Kenntnisse verfügen. Wie geht man mit ordinalen oder dichtomen Variablen um? Wie mit einer Verletzung der Nomalverteilungsannahme? In vielen Forschungskontexten steht die Betrachtung mehrerer Gruppen im Vordergrund, andernorts sucht man nach Modellen zur Kombination von Strukturgleichungs-, Mehrebenen- und Latent-Class-Modellen. Darüber hinaus setzen Forscher verstärkt moderne Methoden zum Umgang mit fehlenden Daten sowie Stichproben- und Teststärkeplanung ein. Diese und weitere Fragen werden praxisnah und Schritt für Schritt erläutert.

Datenanalyse Mit Mplus

Author: Christian Geiser
Publisher: Springer-Verlag
ISBN: 353193192X
Size: 62.11 MB
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Strukturgleichungsmodelle gehören mittlerweile zu den etablierten statistischen Methoden in den Sozialwissenschaften und eignen sich für die Beantwortung einer Vielzahl von Fragestellungen. Das Analyseprogramm Mplus erfreut sich als eines der aktuellsten, flexibelsten und anwenderfreundlichsten Statistikprogramme zunehmender Beliebtheit. Praxisnah, mit zahlreichen Beispielen, Probedatensätzen und Abbildungen führt der Autor Schritt für Schritt in die Grundlagen der Handhabung von Mplus (Version 5) ein, und beschreibt die Anwendung grundlegender Analyseverfahren. Dabei werden nicht nur konventionelle Strukturgleichungsmodelle, sondern auch Strukturgleichungsmodelle der Veränderungsmessung sowie Mehrebenenregressionsmodelle und Latent-Class-Analysen besprochen.

Strukturgleichungsmodelle Mit Mplus

Author: Oliver Christ
Publisher: Walter de Gruyter
ISBN: 3486714805
Size: 13.20 MB
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Strukturgleichungsmodelle eignen sich hervorragend für die empirische Analyse zahlreicher theoretischer Fragestellungen und stellen somit für die Sozialwissenschaften eine unverzichtbare statistische Methode dar. Mit Mplus steht seit einiger Zeit ein besonders flexibles und anwenderfreundliches Statistikprogramm für die Strukturgleichungsmodellierung zur Verfügung. Dieses Lehrbuch vermittelt den Lesern ein umfassendes Verständnis grundlegender und weiterführender Anwendungen von Strukturgleichungsmodellen in Mplus.

Longitudinal Data Analysis

Author: Jason Newsom
Publisher: Routledge
ISBN: 1136705465
Size: 31.85 MB
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This book provides accessible treatment to state-of-the-art approaches to analyzing longitudinal studies. Comprehensive coverage of the most popular analysis tools allows readers to pick and choose the techniques that best fit their research. The analyses are illustrated with examples from major longitudinal data sets including practical information about their content and design. Illustrations from popular software packages offer tips on how to interpret the results. Each chapter features suggested readings for additional study and a list of articles that further illustrate how to implement the analysis and report the results. Syntax examples for several software packages for each of the chapter examples are provided at Although many of the examples address health or social science questions related to aging, readers from other disciplines will find the analyses relevant to their work. In addition to demonstrating statistical analysis of longitudinal data, the book shows how to interpret and analyze the results within the context of the research design. The methods covered in this book are applicable to a range of applied problems including short- to long-term longitudinal studies using a range of sample sizes. The book provides non-technical, practical introductions to the concepts and issues relevant to longitudinal analysis. Topics include use of publicly available data sets, weighting and adjusting for complex sampling designs with longitudinal studies, missing data and attrition, measurement issues related to longitudinal research, the use of ANOVA and regression for average change over time, mediation analysis, growth curve models, basic and advanced structural equation models, and survival analysis. An ideal supplement for graduate level courses on data analysis and/or longitudinal modeling taught in psychology, gerontology, public health, human development, family studies, medicine, sociology, social work, and other behavioral, social, and health sciences, this multidisciplinary book will also appeal to researchers in these fields.

Longitudinal Structural Equation Modeling

Author: Todd D. Little
Publisher: Guilford Press
ISBN: 1462510167
Size: 57.49 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 (http: // 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).

Handbook Of Developmental Research Methods

Author: Brett Laursen
Publisher: Guilford Press
ISBN: 1609189515
Size: 24.71 MB
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Appropriate for use in developmental research methods or analysis of change courses, this is the first methods handbook specifically designed to meet the needs of those studying development. Leading developmental methodologists present cutting-edge analytic tools and describe how and when to use them, in accessible, nontechnical language. They also provide valuable guidance for strengthening developmental research with designs that anticipate potential sources of bias. Throughout the chapters, research examples demonstrate the procedures in action and give readers a better understanding of how to match research questions to developmental methods. The companion website ( supplies data and program syntax files for many of the chapter examples.

Growth Modeling

Author: Kevin J. Grimm
Publisher: Guilford Publications
ISBN: 1462526071
Size: 16.79 MB
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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 R), discussion of the output, and interpretation of each model's results. User-Friendly Features *Real, worked-through longitudinal data examples serving as illustrations in each chapter. *Script boxes that provide code for fitting the models to example data and facilitate application to the reader's own data. *"Important Considerations" sections offering caveats, warnings, and recommendations for the use of specific models. *Companion website supplying datasets and syntax for the book's examples, along with additional code in SAS/R for linear mixed-effects modeling.

Confirmatory Factor Analysis For Applied Research Second Edition

Author: Timothy A. Brown
Publisher: Guilford Publications
ISBN: 1462515363
Size: 70.97 MB
Format: PDF
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This accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA) for its emphasis on practical and conceptual aspects rather than mathematics or formulas. Detailed, worked-through examples drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology. The text shows how to formulate, program, and interpret CFA models using popular latent variable software packages (LISREL, Mplus, EQS, SAS/CALIS); understand the similarities ...