
eBook - PDF
Categorical Data Analysis with Structural Equation Models
Applications in Mplus and lavaan
- 363 pages
- English
- PDF
- Available on iOS & Android
eBook - PDF
Categorical Data Analysis with Structural Equation Models
Applications in Mplus and lavaan
About this book
Multivariate categorical outcomes, such as Likert scale responses and disease diagnoses, require specialized structural equation modeling (SEM) software to be analyzed properly. Providing needed skills for applied researchers and graduate students, this book leads readers from regression analysis with categorical outcomes to complex SEMs with latent variables for categorical indicators. The initial section sets the stage by demonstrating regression analyses for binary, ordered, or count outcomes using R. Chapters then reanalyze the same data using Mplus and R lavaan to show how univariate models for categorical outcomes can be estimated and interpreted with SEM programs. Subsequently, the book turns to multivariate models, discussing path models, confirmatory factor models, and latent variable path models with categorical outcomes. Concluding chapters cover advanced SEM with categorical outcomes, including growth models, latent class models, and survival models. Worked-through examples are featured throughout. The companion website provides R (including lavaan), Mplus, and SAS code, as applicable, for the examples.
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Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Yes, you can access Categorical Data Analysis with Structural Equation Models by Kevin J. Grimm in PDF and/or ePUB format, as well as other popular books in Social Sciences & Statistics for Business & Economics. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Cover
- Half Title Page
- Series Page
- Title Page
- Copyright
- Dedication
- Series Editor’s Note
- Preface
- Contents
- 1. Regression, Structural Equation Modeling, Mplus, and lavaan
- Part I. Regression Analysis with Categorical Outcomes in R
- Part II. Regression Analysis with Structural Equation Modeling Programs
- Part III. Structural Equation Models and Applications
- Part IV. Advanced Structural Equation Models and Applications
- References
- Author Index
- Subject Index
- About the Author