Regression Modeling Strategies - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Regression Modeling Strategies write by Frank E. Harrell. This book was released on 2013-03-09. Regression Modeling Strategies available in PDF, EPUB and Kindle. Many texts are excellent sources of knowledge about individual statistical tools, but the art of data analysis is about choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for dealing with nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with "too many variables to analyze and not enough observations," and powerful model validation techniques based on the bootstrap. This text realistically deals with model uncertainty and its effects on inference to achieve "safe data mining".
Regression Modeling Strategies
Regression Modeling Strategies - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Regression Modeling Strategies write by Frank E. Harrell. This book was released on 2001-06-15. Regression Modeling Strategies available in PDF, EPUB and Kindle. This book presents information on regressions modeling strategies that address many issues arising when developing multivariable models using (real data) examples. It includes imputation methods for dealing with missing data effectively, methods for dealing with nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with “too many variables to analyze and not enough observations”, and powerful model validation techniques based on the bootstrap. The text deals with model uncertainty and its effect on inference. It also presents many graphical methods for communicating complex regression models to nonstatisticians.
Regression Modeling Strategies
Regression Modeling Strategies - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Regression Modeling Strategies write by Frank E. Harrell. This book was released on 2014-01-15. Regression Modeling Strategies available in PDF, EPUB and Kindle.
Regression Modeling Strategies
Regression Modeling Strategies - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Regression Modeling Strategies write by Frank E. Harrell , Jr.. This book was released on 2015-08-14. Regression Modeling Strategies available in PDF, EPUB and Kindle. This highly anticipated second edition features new chapters and sections, 225 new references, and comprehensive R software. In keeping with the previous edition, this book is about the art and science of data analysis and predictive modelling, which entails choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasises problem solving strategies that address the many issues arising when developing multi-variable models using real data and not standard textbook examples. Regression Modelling Strategies presents full-scale case studies of non-trivial data-sets instead of over-simplified illustrations of each method. These case studies use freely available R functions that make the multiple imputation, model building, validation and interpretation tasks described in the book relatively easy to do. Most of the methods in this text apply to all regression models, but special emphasis is given to multiple regression using 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 using 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 ordinary multiple regression and intermediate algebra. The book will also serve as a reference for data analysts and statistical methodologists, as it contains an up-to-date survey and bibliography of modern statistical modelling techniques.
Applied Regression Modeling
Applied Regression Modeling - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Applied Regression Modeling write by Iain Pardoe. This book was released on 2013-01-07. Applied Regression Modeling available in PDF, EPUB and Kindle. Praise for the First Edition "The attention to detail is impressive. The book is very well written and the author is extremely careful with his descriptions . . . the examples are wonderful." —The American Statistician Fully revised to reflect the latest methodologies and emerging applications, Applied Regression Modeling, Second Edition continues to highlight the benefits of statistical methods, specifically regression analysis and modeling, for understanding, analyzing, and interpreting multivariate data in business, science, and social science applications. The author utilizes a bounty of real-life examples, case studies, illustrations, and graphics to introduce readers to the world of regression analysis using various software packages, including R, SPSS, Minitab, SAS, JMP, and S-PLUS. In a clear and careful writing style, the book introduces modeling extensions that illustrate more advanced regression techniques, including logistic regression, Poisson regression, discrete choice models, multilevel models, and Bayesian modeling. In addition, the Second Edition features clarification and expansion of challenging topics, such as: Transformations, indicator variables, and interaction Testing model assumptions Nonconstant variance Autocorrelation Variable selection methods Model building and graphical interpretation Throughout the book, datasets and examples have been updated and additional problems are included at the end of each chapter, allowing readers to test their comprehension of the presented material. In addition, a related website features the book's datasets, presentation slides, detailed statistical software instructions, and learning resources including additional problems and instructional videos. With an intuitive approach that is not heavy on mathematical detail, Applied Regression Modeling, Second Edition is an excellent book for courses on statistical regression analysis at the upper-undergraduate and graduate level. The book also serves as a valuable resource for professionals and researchers who utilize statistical methods for decision-making in their everyday work.
