Screen LibraryHandbook of regression analysis with applications in R /
"Building on the Handbook of Regression Analysis and Regression Analysis by Example, the authors' thorough treatments of "classic" regression analysis, this book covers two important and more advanced topics of time-to-event survival data and longitudinal and clustered data. Furt...
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| Main Authors: | |
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| Published: |
John Wiley & Sons, Inc.,
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| Publisher Address: | Hoboken, NJ : |
| Publication Dates: | 2020. |
| Literature type: | Book |
| Language: | English |
| Edition: | Second edition. |
| Series: |
Wiley series in probability and statistics
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| Subjects: | |
| Summary: |
"Building on the Handbook of Regression Analysis and Regression Analysis by Example, the authors' thorough treatments of "classic" regression analysis, this book covers two important and more advanced topics of time-to-event survival data and longitudinal and clustered data. Further, methods that have become prominent in the last 15-30 years that are designed for analyses on often-large data sets and can take advantage of exibility in modeling were not covered, including smoothing, tree- based, and regularization methods, all of which are increasingly becoming part of the data analysis toolkit. Examples are drawn from a wide variety of application areas using real data sets and all of the R code is provided. The book will be of interest to data scientists as well as in regression analysis courses at the graduate and undergraduate level. Regression analysis is a statistical process for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables. More specifically, regression analysis helps one understand how the typical value of the dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed. Most commonly, regression analysis estimates the conditional expectation of the dependent variable given the independent variables -- that is, the average value of the dependent variable when the independent variables are fixed. Regression analysis is widely used for prediction and forecasting, where its use has substantial overlap with the field of machine learning"-- |
| Item Description: | Revised edition of: Handbook of regression analysis. 2013. |
| Carrier Form: | xxii, 349 pages : illustrations ; 24 cm. |
| Bibliography: | Includes bibliographical references (pages 337-342) and index. |
| ISBN: |
9781119392378 1119392373 |
| Index Number: | QA278 |
| CLC: | O212.1-62 |
| Call Number: | O212.1-62/C495/2nd ed. |
| Contents: | Multiple linear regression -- Model building -- Diagnostics for unusual observations -- Transformations and linearizable models -- Time series data and autocorrelation -- Analysis of variance -- Analysis of covariance -- Logistic regression -- Multinomial regression -- Count regression -- Models for time-to-event (survival) data -- Nonlinear regression -- Models for longitudinal and nested data -- Regularization methods and sparse models -- Smoothing and additive models -- Tree-based models. |