000			03403nam a22002777a 4500
001			20240826104908.0
003			20240826104908.0
005			20240826105549.0
008			240826b |||||||| |||| 00| 0 eng d
020			_a978-3-319-31243-9
020			_a978-3-319-31245-3
022			_a2197-5736
022			_a2197-5744
040			_cddc
041			_aEnglish
100			_qDirk F. Moore
245			_aApplied Survival Analysis Using R
260			_aPiscataway, NJ, USA : _bSpringer International Publishing Switzerland : _c2016
300			_a234 Pages
300			_aIncludes References and Index
490			_aUse R!
520			_aApplied 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 textbooks 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.
600			_xBiometry, Epidemiology, Mathematics / Probability & Statistics / General, Medical / Biostatistics, Medical / Epidemiology, Medical / General, Science / Life Sciences / General, Statistics, Science / Life Sciences / Biology, Failure time data analysis, Survival analysis (Biometry).
856			_uDOI 10.1007/978-3-319-31245-3 _yDOI 10.1007/978-3-319-31245-3
942			_2ddc _cEB _n0
999			_c28430 _d28430