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Longitudinal data analysis for the behavioral sciences using R / Jeffrey D. Long

Por: Long, Jeffrey D [autor].
Tipo de material: Libro impreso(a) Libro impreso(a) Editor: Los Angeles, California, United States: Sage Publications, 2012Descripción: xxii, 542 páginas ; 27 centímetros.ISBN: 1412982685; 9781412982689.Tema(s): R (Lenguaje de programación para computadora) | Método longitudinal | Estadística matemática | Procesamiento de datos | Ciencias socialesClasificación: 300.2855133 / L6 Nota de bibliografía: Incluye bibliografía (página 525-534 e índice (página 535-542 Número de sistema: 59706Contenidos:Mostrar Resumen:
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This book is unique in its focus on showing students in the behavioral sciences how to analyze longitudinal data using R software. The book focuses on application, making it practical and accessible to students in psychology, education, and related fields, who have a basic foundation in statistics. It provides explicit instructions in R computer programming throughout the book, showing students exactly how a specific analysis is carried out and how output is interpreted.
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Acervo General (AG) 		Acervo General 300.2855133 L6 Disponible ECO020013873

Incluye bibliografía (página 525-534 e índice (página 535-542

About the Author.. Preface.. Chapter 1. Introduction.. Chapter 2. Brief Introduction to R.. Chapter 3. Data Structures and Longitudinal Analysis.. Chapter 4. Graphing Longitudinal Data.. Chapter 5. Introduction to Linear Mixed Effects Regression.. Chapter 6. Overview of Maximum Likelihood Estimation.. Chapter 7. Multimodel Inference and Akaike's Information Criterion.. Chapter 8. Likelihood Ratio Test.. Chapter 9. Selecting Time Predictors.. Chapter 10. Selecting Random Effects.. Chapter 11. Extending Linear Mixed Effects Regression.. Chapter 12. Modeling Nonlinear Change.. Chapter 13. Advanced Topics.. Appendix: Soft Introduction to Matrix Algebra.. References.. Author Index.. Subject Index

This book is unique in its focus on showing students in the behavioral sciences how to analyze longitudinal data using R software. The book focuses on application, making it practical and accessible to students in psychology, education, and related fields, who have a basic foundation in statistics. It provides explicit instructions in R computer programming throughout the book, showing students exactly how a specific analysis is carried out and how output is interpreted. eng

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