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Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis (Springer Series in Statistics)

Amazon.com Price:  $64.86 (as of 01/05/2019 14:44 PST- Details)

Description

This highly anticipated second edition features new chapters and sections, 225 new references, and comprehensive R software. Consistent with the previous edition, this book is about the art and science of data analysis and predictive modelling, which entails choosing and the usage of a couple of tools. As an alternative of presenting isolated techniques, this text emphasises problem solving strategies that address the many issues arising when developing multi-variable models the usage of real data and not standard textbook examples. 

Regression Modelling Strategies presents full-scale case studies of non-trivial data-sets As an alternative of over-simplified illustrations of each and every method. These case studies use freely to be had R functions that make the a couple of imputation, model building, validation and interpretation tasks described in the book quite easy to do. A few of the methods in this text apply to all regression models, but special emphasis is given to a couple of regression the usage of generalised least squares for longitudinal data, the binary logistic model, models for ordinal responses, parametric survival regression models and the Cox semi parametric survival model. A new emphasis is given to the robust analysis of continuous dependent variables the usage of ordinal regression.

As in the first edition, this text is intended for Masters’ or PhD. level graduate students who have had a general introductory probability and statistics course and who are well versed in strange a couple of regression and intermediate algebra. The book will also serve as a reference for data analysts and statistical methodologists, as it comprises an up-to-date survey and bibliography of modern statistical modelling techniques. 

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