Data Analysis Using Regression and Multilevel / Hierarchical Models Gelman Andrew Columbia University New York
Data Analysis Using Regression and Multilevel / Hierarchical Models Gelman Andrew Columbia University New York Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive…
Specifikacia Data Analysis Using Regression and Multilevel / Hierarchical Models Gelman Andrew Columbia University New York
Data Analysis Using Regression and Multilevel / Hierarchical Models Gelman Andrew Columbia University New York
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 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. 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.
Practical tips regarding building, fitting, and understanding are provided throughout. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Author resource page: http:
Bayesian Data Analysis Gelman Andrew