Survival Analysis in Medicine and Genetics

Jialiang Li is an associate professor in the Department of Statistics and Applied Probability at the National University of Singapore, an associate professor at the Duke-NUS Graduate Medical School, and a scientist at the Singapore Eye Research Institute. He is on the editorial board of Biometrics and has published 70 peer-reviewed research papers in scientific journals. He has been a recipient the Young Scientist Award from the National University of Singapore and the New Investigator Grant and Cooperative Basic Research Grant from the National Medical Research Council.Shuangge Ma is an associate professor in the Department of Biostatistics, Yale School of Public Health at Yale University. He earned a PhD in statistics from the University of Wisconsin and completed postdoctoral training in the Department of Biostatistics at the University of Washington. His research interests include survival analysis, semiparametric methods, bioinformatics, cancer studies, and health economics.

". . . this book contains an excellent theoretical coverage of interval censored data, and deals with other topics relevant for survival analysis in a comprehensive but summarized way."—Victor Moreno, International Society for Clinical Biostatistics"This book provides a new outlook on survival analysis methods by emphasizing the application of the statistical methods for biological and genetic problems. … this book covers several important and specific topics, which have been rarely covered in other conventional survival textbooks. Throughout this book, many advanced statistical methods are well specified so that biostatisticians and researchers in the fields of medicine and genetics can easily understand and apply these methods to complicated survival data with high-dimensional covariates."—Seungyeoun Lee, Biometrics"The great strength of the book lies in its comprehensive treatment of both classical and novel methods, covering almost all aspects of survival analysis that biostatisticians are confronted with in everyday practice. The text is very well organised, and both writing style and notation are remarkably homogeneous. The readers will appreciate the inclusion of clinical studies as applications in the book."—P. G. Sankaran, Cochin University of Science and Technology

• Introduction: Examples and Basic Principles. Analysis Trilogy: Estimation, Test, and Regression. Analysis of Interval Censored Data. Special Modeling Methodology. Diagnostic Medicine for Survival Analysis. Survival Analysis with High-Dimensional Covariates. Bibliography. Index.