Data Analysis Using Regression and Multilevel/Hierarchical Models

Description

Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout. Author resource page: http://www.stat.columbia.edu/~gelman/arm/

Disclaimer:
Contents of this page are indexed from the Internet. All actions are under your responsability. Email us to report illegal contents or external links and we'll remove them immediately.

Please check the description for download links if any or do a search to find alternative books.

Can't Download?
Please search mirrors if you can't find download links for "Data Analysis Using Regression and Multilevel/Hierarchical Models" in "Description" and someone else may update the links. Check the comments when back to find any updates.

Search Mirrors
Maybe some mirror pages will be helpful, search this book at top of this page or click here to find more info.

1. Ebooks list page : 2115
2. Data Analysis Using Regression and Multilevel/Hierarchical Models
3. Data Analysis Using Regression and Multilevel/Hierarchical Models
4. Multilevel Analysis for Applied Research: It's Just Regression!
5. Multilevel Analysis for Applied Research: It's Just Regression!
6. Multilevel Analysis for Applied Research: It's Just Regression! (Methodology In The Social Sciences)
7. Hierarchical Modeling and Inference in Ecology: The Analysis of Data from Populations, Metapopulations and Communities
8. Regression Analysis of Count Data
9. [share_ebook] Regression Models for Time Series Analysis
10. Applied Survival Analysis: Regression Modeling of Time to Event Data
11. [request_ebook] Applied Regression Analysis and Generalized Linear Models
12. [share_ebook] Analysis of Variance for Random Models, Volume 2: Unbalanced Data: Theory, Methods, Applications, and Data Analysis
13. Fitting Models to Biological Data Using Linear and Nonlinear Regression: A Practical Guide to Curve Fitting
14. Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation Models
15. Market Models: A Guide to Financial Data Analysis
16. Statistical Analysis of Network Data: Methods and Models