Discovering Structural Equation Modeling Using Stata 13 (Revised Edition) PDF Download
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Author: Alan C. Acock
Publisher: Stata Press
ISBN: 9781597181396
Category : Mathematics
Languages : en
Pages : 306
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Book Description
Discovering Structural Equation Modeling Using Stata, Revised Edition is devoted to Stata’s sem command and all it can do. Learn about its capabilities in the context of confirmatory factor analysis, path analysis, structural equation modeling, longitudinal models, and multiple-group analysis. Each model is presented along with the necessary Stata code, which is parsimonious, powerful, and can be modified to fit a wide variety of models. The datasets used are downloadable, offering a hands-on approach to learning. A particularly exciting feature of Stata is the SEM Builder. This graphical interface for structural equation modeling allows you to draw publication-quality path diagrams and fit the models without writing any programming code. When you fit a model with the SEM Builder, Stata automatically generates the complete code that you can save for future use. Use of this unique tool is extensively covered in an appendix and brief examples appear throughout the text.
Author: Alan C. Acock
Publisher: Stata Press
ISBN: 9781597181396
Category : Mathematics
Languages : en
Pages : 306
Get Book
Book Description
Discovering Structural Equation Modeling Using Stata, Revised Edition is devoted to Stata’s sem command and all it can do. Learn about its capabilities in the context of confirmatory factor analysis, path analysis, structural equation modeling, longitudinal models, and multiple-group analysis. Each model is presented along with the necessary Stata code, which is parsimonious, powerful, and can be modified to fit a wide variety of models. The datasets used are downloadable, offering a hands-on approach to learning. A particularly exciting feature of Stata is the SEM Builder. This graphical interface for structural equation modeling allows you to draw publication-quality path diagrams and fit the models without writing any programming code. When you fit a model with the SEM Builder, Stata automatically generates the complete code that you can save for future use. Use of this unique tool is extensively covered in an appendix and brief examples appear throughout the text.
Author: Alan C. Acock
Publisher:
ISBN: 9781597181778
Category : Stata
Languages : en
Pages :
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Book Description
Discovering Structural Equation Modeling Using Stata is devoted to Stata's sem command and all it can do. Learn about its capabilities in the context of confirmatory factor analysis, path analysis, structural equation modeling, longitudinal models, and multiple-group analysis. Each model covered is presented along with the necessary Stata code, which is parsimonious, powerful, and can be modified to fit a wide variety of models. The datasets used are downloadable, and you are encouraged to run the programs in a hands-on approach to learning. A particularly exciting feature of Stata is the SEM builder. This graphic interface for structural equation modeling allows you to draw publication-quality path diagrams and to fit the models without writing any programming code. When you fit a model with the SIM builder, Stata automatically generates the complete code that you can save for future use. Use of this unique tool is extensively covered in an appendix, and brief examples appear throughout the text. A miminal background in multiple regression is sufficient to benefit from this text. While it would be helpful to have some experience with Stata, it is not essential. Though the primary audience is those who are new to structural equation modeling, those who are already familiar with it will find this text useful for the Stata code it covers. Overall, the text is intended to be practical and will serve as a useful reference --
Author: Alan C. Acock
Publisher: Stata Press
ISBN: 9781597181334
Category : Mathematics
Languages : en
Pages : 0
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Book Description
Discovering Structural Equation Modeling Using Stata is devoted to Stata’s sem command and all it can do. You’ll learn about its capabilities in the context of confirmatory factor analysis, path analysis, structural equation modeling, longitudinal models, and multiple-group analysis. The book describes each model along with the necessary Stata code, which is parsimonious, powerful, and can be modified to fit a wide variety of models. Downloadable data sets enable you to run the programs and learn in a hands-on way. A particularly exciting feature of Stata is the SEM Builder. This graphic interface for structural equation modeling allows you to draw publication-quality path diagrams and fit the models without writing any programming code. When you fit a model with the SEM Builder, Stata automatically generates the complete code that you can save for future use. Use of this unique tool is extensively covered in an appendix, and brief examples appear throughout the text. Requiring minimal background in multiple regression, this practical reference is designed primarily for those new to structural equation modeling. Some experience with Stata would be helpful but is not essential. Readers already familiar with structural equation modeling will also find the book’s State code useful.
Author: Anders Skrondal
Publisher: CRC Press
ISBN: 0203489438
Category : Mathematics
Languages : en
Pages : 528
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Book Description
This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models. Following a gentle introduction to latent variable modeling, the authors clearly explain and contrast a wi
Author: Adam Davey
Publisher: Routledge
ISBN: 1135269300
Category : Psychology
Languages : en
Pages : 328
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Book Description
Statistical power analysis has revolutionized the ways in which we conduct and evaluate research. Similar developments in the statistical analysis of incomplete (missing) data are gaining more widespread applications. This volume brings statistical power and incomplete data together under a common framework, in a way that is readily accessible to those with only an introductory familiarity with structural equation modeling. It answers many practical questions such as: How missing data affects the statistical power in a study How much power is likely with different amounts and types of missing data How to increase the power of a design in the presence of missing data, and How to identify the most powerful design in the presence of missing data. Points of Reflection encourage readers to stop and test their understanding of the material. Try Me sections test one’s ability to apply the material. Troubleshooting Tips help to prevent commonly encountered problems. Exercises reinforce content and Additional Readings provide sources for delving more deeply into selected topics. Numerous examples demonstrate the book’s application to a variety of disciplines. Each issue is accompanied by its potential strengths and shortcomings and examples using a variety of software packages (SAS, SPSS, Stata, LISREL, AMOS, and MPlus). Syntax is provided using a single software program to promote continuity but in each case, parallel syntax using the other packages is presented in appendixes. Routines, data sets, syntax files, and links to student versions of software packages are found at www.psypress.com/davey. The worked examples in Part 2 also provide results from a wider set of estimated models. These tables, and accompanying syntax, can be used to estimate statistical power or required sample size for similar problems under a wide range of conditions. Class-tested at Temple, Virginia Tech, and Miami University of Ohio, this brief text is an ideal supplement for graduate courses in applied statistics, statistics II, intermediate or advanced statistics, experimental design, structural equation modeling, power analysis, and research methods taught in departments of psychology, human development, education, sociology, nursing, social work, gerontology and other social and health sciences. The book’s applied approach will also appeal to researchers in these areas. Sections covering Fundamentals, Applications, and Extensions are designed to take readers from first steps to mastery.
Author: Indranarain Ramlall
Publisher: Emerald Group Publishing
ISBN: 1786358824
Category : Education
Languages : en
Pages : 152
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Book Description
This book explains in a rigorous, concise and practical manner all the vital components embedded in structural equation modelling. Focusing on R and stata to implement and perform various structural equation models.
Author: MICHAEL N. MITCHELL
Publisher: Stata Press
ISBN: 9781597183215
Category :
Languages : en
Pages : 610
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Book Description
Interpreting and Visualizing Regression Models Using Stata, Second Edition provides clear and simple examples illustrating how to interpret and visualize a wide variety of regression models. Including over 200 figures, the book illustrates linear models with continuous predictors (modeled linearly, using polynomials, and piecewise), interactions of continuous predictors, categorical predictors, interactions of categorical predictors, and interactions of continuous and categorical predictors. The book also illustrates how to interpret and visualize results from multilevel models, models where time is a continuous predictor, models with time as a categorical predictor, nonlinear models (such as logistic or ordinal logistic regression), and models involving complex survey data. The examples illustrate the use of the margins, marginsplot, contrast, and pwcompare commands. This new edition reflects new and enhanced features added to Stata, most importantly the ability to label statistical output using value labels associated with factor variables. As a result, output regarding marital status is labeled using intuitive labels like Married and Unmarried instead of using numeric values such as 1 and 2. All the statistical output in this new edition capitalizes on this new feature, emphasizing the interpretation of results based on variables labeled using intuitive value labels. Additionally, this second edition illustrates other new features, such as using transparency in graphics to more clearly visualize overlapping confidence intervals and using small sample-size estimation with mixed models. If you ever find yourself wishing for simple and straightforward advice about how to interpret and visualize regression models using Stata, this book is for you.
Author: Xing Liu
Publisher: SAGE Publications
ISBN: 1483319768
Category : Social Science
Languages : en
Pages : 372
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Book Description
The first book to provide a unified framework for both single-level and multilevel modeling of ordinal categorical data, Applied Ordinal Logistic Regression Using Stata helps readers learn how to conduct analyses, interpret the results from Stata output, and present those results in scholarly writing. Using step-by-step instructions, this non-technical, applied book leads students, applied researchers, and practitioners to a deeper understanding of statistical concepts by closely connecting the underlying theories of models with the application of real-world data using statistical software. An open-access website for the book contains data sets, Stata code, and answers to in-text questions.
Author: College Station Stata Corporation
Publisher:
ISBN: 9781597180979
Category : Social sciences
Languages : en
Pages : 294
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Book Description
Author: Alan C. Acock
Publisher: Stata Press
ISBN: 9781597181099
Category : Mathematics
Languages : en
Pages : 0
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Book Description
Updated to reflect the new features of Stata 11, A Gentle Introduction to Stata, Third Edition continues to help new Stata users become proficient in Stata. After reading this introductory text, you will be able to enter, build, and manage a data set as well as perform fundamental statistical analyses. New to the Third Edition A new chapter on the analysis of missing data and the use of multiple-imputation methods Extensive revision of the chapter on ANOVA Additional material on the application of power analysis The book covers data management; good work habits, including the use of basic do-files; basic exploratory statistics, including graphical displays; and analyses using the standard array of basic statistical tools, such as correlation, linear and logistic regression, and parametric and nonparametric tests of location and dispersion. Rather than splitting these topics by their Stata implementation, the material on graphics and postestimation are woven into the text in a natural fashion. The author teaches Stata commands by using the menus and dialog boxes while still stressing the value of do-files. Each chapter includes exercises and real data sets are used throughout.
