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Sto caricando le informazioni... Data Analysis Using Regression and Multilevel/Hierarchical Modelsdi Andrew Gelman
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Iscriviti per consentire a LibraryThing di scoprire se ti piacerà questo libro. Attualmente non vi sono conversazioni su questo libro. One of the best books on multi-level models. It was a great read and I loved the examples. ( ) A good comprehensive survey of the topics. But, different sections assume different levels of background knowledge, from nearly nothing to grad-level statistics theory. I like their views on the relative importance of modeling vs. hypothesis testing, and in particular the emphasis on graphs/visualization. Also like the use of R/lmer and BUGS, and am sympathetic to their somewhat critical view of the terminology of mixed-effects models, despite the close connection to their preferred Bayesian view. nessuna recensione | aggiungi una recensione
Appartiene alle Serie
Data Analysis Using Regression and Multilevel/Hierarchical Models, first published in 2007, 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. Non sono state trovate descrizioni di biblioteche |
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Google Books — Sto caricando le informazioni... GeneriSistema Decimale Melvil (DDC)519.536Natural sciences and mathematics Mathematics Applied Mathematics, Probabilities Statistical MathematicsClassificazione LCVotoMedia:
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