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010 _a 2019759087
020 _a9783319312453
024 7 _a10.1007/978-3-319-31245-3
_2doi
035 _a(DE-He213)978-3-319-31245-3
040 _aDLC
_beng
_epn
_erda
_cDLC
050 _aQA276.4. M819 2016
072 7 _aMBNS
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072 7 _aMED090000
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082 0 4 _a519.5
_223
100 1 _aMoore, Dirk F,
_eauthor.
245 1 0 _aApplied Survival Analysis Using R /
_cby Dirk F. Moore.
250 _a1st ed. 2016.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _axiv, 226 pages 66 illustrations, 26 illustrations in color.)
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aUse R!,
_x2197-5736
505 0 _aIntroduction -- Basic Principles of Survival Analysis -- Nonparametric Survival Curve Estimation -- Nonparametric Comparison of Survival Distributions -- Regression Analysis Using the Proportional Hazards Model -- Model Selection and Interpretation -- Model Diagnostics -- Time Dependent Covariates -- Multiple Survival Outcomes and Competing Risks -- Parametric Models -- Sample Size Determination for Survival Studies -- Additional Topics -- References -- Appendix A -- Index -- R Package Index.
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 R Organized via basic concepts and most frequently used procedures, with advanced topics toward the end of the book and in appendices Includes 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.
588 _aDescription based on publisher-supplied MARC data.
650 0 _aBiostatistics.
650 0 _aEpidemiology.
650 0 _aStatistics.
650 1 4 _aStatistics for Life Sciences, Medicine, Health Sciences.
_0https://scigraph.springernature.com/ontologies/product-market-codes/S17030
650 2 4 _aBiostatistics.
_0https://scigraph.springernature.com/ontologies/product-market-codes/L15020
650 2 4 _aEpidemiology.
_0https://scigraph.springernature.com/ontologies/product-market-codes/H63000
650 2 4 _aStatistical Theory and Methods.
_0https://scigraph.springernature.com/ontologies/product-market-codes/S11001
776 0 8 _iPrint version:
_tApplied survival analysis using R.
_z9783319312439
_w(DLC) 2016940055
776 0 8 _iPrinted edition:
_z9783319312439
776 0 8 _iPrinted edition:
_z9783319312446
830 0 _aUse R!,
_x2197-5736
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