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Applied regression and multilevel/hierarchical models

Author: Andrew Gelman; Jennifer Hill
Publisher: Cambridge ; New York : Cambridge University Press, 2006.
Series: Analytical methods for social research.
Edition/Format:   Print book : English
Database:WorldCat
Summary:

This book, first published in 2007, is for the applied researcher performing data analysis using linear and nonlinear regression and multilevel models.

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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Andrew Gelman; Jennifer Hill
ISBN: 0521867061 9780521867061 052168689X 9780521686891
OCLC Number: 156588530
Description: pages cm.
Contents: 1. Why?; 2. Concepts and methods from basic probability and statistics; Part I. A. Single-Level Regression: 3. Linear regression: the basics; 4. Linear regression: before and after fitting the model; 5. Logistic regression; 6. Generalized linear models; Part I. B. Working with Regression Inferences: 7. Simulation of probability models and statistical inferences; 8. Simulation for checking statistical procedures and model fits; 9. Causal inference using regression on the treatment variable; 10. Causal inference using more advanced models; Part II. A. Multilevel Regression: 11. Multilevel structures; 12. Multilevel linear models: the basics; 13. Multilevel linear models: varying slopes, non-nested models and other complexities; 14. Multilevel logistic regression; 15. Multilevel generalized linear models; Part II. B. Fitting Multilevel Models: 16. Multilevel modeling in bugs and R: the basics; 17. Fitting multilevel linear and generalized linear models in bugs and R; 18. Likelihood and Bayesian inference and computation; 19. Debugging and speeding convergence; Part III. From Data Collection to Model Understanding to Model Checking: 20. Sample size and power calculations; 21. Understanding and summarizing the fitted models; 22. Analysis of variance; 23. Causal inference using multilevel models; 24. Model checking and comparison; 25. Missing data imputation; Appendixes: A. Six quick tips to improve your regression modeling; B. Statistical graphics for research and presentation; C. Software; References.
Series Title: Analytical methods for social research.
Responsibility: Andrew Gelman, Jennifer Hill.
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'Data Analysis Using Regression and Multilevel/Hierarchical Models' ... careful yet mathematically accessible style is generously illustrated with examples and graphical displays, making it ideal for Read more...

 
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