
Applied Survival Analysis Using R covers the main principles of survival analysis gives examples of how it is applied & 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 & studies of animals Many survival methods are extensions of techniques used in linear regression & 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 & truncation model variable selection & residual analysis Because explaining survival analysis requires more advanced mathematics than many other statistical topics this book is organized with basic concepts & most frequently used procedures covered in earlier chapters with more advanced topics near the end & in the appendices A background in basic linear regression & categorical data analysis as well as a basic knowledge of calculus & the R system will help the reader to fully appreciate the information presented Examples are simple & straightforward while still illustrating key points shedding light on the application of survival analysis in a way that is useful for graduate students researchers & practitioners in biostatistics