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Applied Survival Analysis Using R (Use R!) de Dirk F. F. Moore
Descripción - Críticas “This book describes the principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R. … The intended audience includes students taking a master's level course in statistical theory and analysts who need to work with survival time data. … This is an excellent overview of the main principles of survival analysis and its applications with examples using R for the intended audience.” (Hemang B. Panchal, Doody’s Book Reviews, August, 2016) Reseña del editor Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R as a vehicle. Survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical trials, epidemiological studies, and studies of animals. Many survival methods are extensions of techniques used in linear regression and categorical data, while other aspects of this field are unique to survival data. This text employs numerous actual examples to illustrate survival curve estimation, comparison of survivals of different groups, proper accounting for censoring and truncation, model variable selection, and residual analysis.Because explaining survival analysis requires more advanced mathematics than many other statistical topics, this book is organized with basic concepts and most frequently used procedures covered in earlier chapters, with more advanced topics near the end and in the appendices. A background in basic linear regression and categorical data analysis, as well as a basic knowledge of calculus and the R system, will help the reader to fully appreciate the information presented. Examples are simple and straightforward while still illustrating key points, shedding light on the application of survival analysis in a way that is useful for graduate students, researchers, and practitioners in biostatistics. Contraportada Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R as a vehicle. Survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical trials, epidemiological studies, and studies of animals. Many survival methods are extensions of techniques used in linear regression and categorical data, while other aspects of this field are unique to survival data. This text employs numerous actual examples to illustrate survival curve estimation, comparison of survivals of different groups, proper accounting for censoring and truncation, model variable selection, and residual analysis.Because explaining survival analysis requires more advanced mathematics than many other statistical topics, this book is organized with basic concepts and most frequently used procedures covered in earlier chapters, with more advanced topics near the end and in the appendices. A background in basic linear regression and categorical data analysis, as well as a basic knowledge of calculus and the R system, will help the reader to fully appreciate the information presented. Examples are simple and straightforward while still illustrating key points, shedding light on the application of survival analysis in a way that is useful for graduate students, researchers, and practitioners in biostatistics.Clearly illustrates concepts of survival analysis principles and analyzes actual survival data using R, in addition to including an appendix with a basic introduction to ROrganized via basic concepts and most frequently used procedures, with advanced topics toward the end of the book and in appendicesIncludes multiple original data sets that have not appeared in other textbooksDirk F. Moore is Associate Professor of Biostatistics at the Rutgers School of Public Health and the Rutgers Cancer Institute of New Jersey. He received a Ph.D. in biostatistics from the University of Washington in Seattle and, prior to joining Rutgers, was a faculty member in the Statistics Department at Temple University. He has published numerous papers on the theory and application of survival analysis and other biostatistics methods to clinical trials and epidemiology studies. Biografía del autor Dirk F. Moore is Associate Professor of Biostatistics at the Rutgers School of Public Health and the Rutgers Cancer Institute of New Jersey. He received a Ph.D. in biostatistics from the University of Washington in Seattle and, prior to joining Rutgers, was a faculty member in the Statistics Department at Temple University. He has published numerous papers on the theory and application of survival analysis and other biostatistics methods to clinical trials and epidemiology studies.
Applied survival analysis using r book, 2016 worldcat applied survival analysis using r covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using r as a vehicle survival data, where the primary outcome is time to a specific event, Applied survival analysis using r dirk f moore springer applied survival analysis using r covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using r as a vehicle survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical trials, epidemiological studies, and studies of animals Applied survival analysis using r use r moore, dirk f applied survival analysis using r covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using r as a vehicle survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical trials, epidemiological studies, and studies of animals
A handbookofstatisticalanalyses using r 3rdedition breastcancer survival 111 introduction 112 survival analysis 113 analysis using r 1131 gliomaradioimmunotherapy figure 111 leads to the impression that patients treated with the novel radioimmunotherapy survive longer, regardless of the tumor type in order to assess if this informal finding is reliable, we may perform a logrank test via Applied survival analysis using r use r applied survival analysis using r covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using r as a vehicle survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical trials, epidemiological studies, and studies of animals Use software r to do survival analysis and simulation a use software r to do survival analysis and simulation a tutorial mai zhou department of statistics, university of kentucky c gpl 20 copyrighted in this short tutorial we suppose you already have r version 150 or later installed, and know how to start and quit r
Detalles del Libro
- Name: Applied Survival Analysis Using R (Use R!)
- Autor: Dirk F. F. Moore
- Categoria: Libros,Libros universitarios y de estudios superiores,Medicina y ciencias de la salud
- Tamaño del archivo: 17 MB
- Tipos de archivo: PDF Document
- Idioma: Español
- Archivos de estado: AVAILABLE
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Applied survival analysis using r 豆瓣 applied survival analysis using r 作者 dirk f moore 出版社 springer 出版年 2016617 页数 226 定价 usd 5999 装帧 paperback 丛书 use r isbn 9783319312439 Google libros libros haz búsquedas en el mayor catálogo de libros completos del mundo mi colección editores información privacidad términos ayuda Applied survival analysis using r springerlink applied survival analysis using r covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using r as a vehicle survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical trials, epidemiological studies, and studies of animals
Survival analysis in r udemy survival analysis is a sub discipline of statistics it actually has several names in some fields it is called eventtime analysis, reliability analysis or duration analysis r is one of the main tools to perform this sort of analysis thanks to the survival package in this course you will learn how to use r to perform survival analysis Applied survival analysis, chapter 5 r textbook examples applied survival analysis, chapter 5 r textbook examples the r packages needed for this chapter is the survival package we currently use r 201 patched version you may want to make sure that packages on your local machine are up to date you can perform updating in r using updatepackages function Applied survival analysis, chapter 2 r textbook examples the r packages needed for this chapter are the survival package and the kmsurv package we currently use r 201 patched version you may want to make sure that packages on your local machine are up to date you can perform update in r using updatepackages function
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