TY  - BOOK
AU  - Tattar,Prabhanjan
AU  - Vaman,H.J.
TI  - Survival analysis
SN  - 9780367030377
AV  - R 853.S7 .V35 2023
U1  - 610.72/4 23/eng/20220513
PY  - 2023///
CY  - Boca Raton, FL
PB  - CRC Press
KW  - Survival analysis (Biometry)
KW  - Clinical trials
KW  - Statistical methods
N1  - Includes bibliographical references and index; Lifetime data and concepts -- Core concepts -- Inference--estimation -- Inference--statistical tests -- Regression models -- Further topics in regression models -- Model selection -- Survival trees -- Ensemble survival analysis -- Neural network survival analysis -- Complementary machine learning techniques
N2  - "Survival analysis generally deals with analysis of data arising from clinical trials. Censoring, truncation, and missing data create analytical challenges and the statistical methods and inference require novel and different approaches for analysis. Statistical properties, essentially asymptotic ones, of the estimators and tests are aptly handled in the counting process framework which is drawn from the larger arm of stochastic calculus. With explosion of data generation during the past two decades, survival data has also enlarged assuming a gigantic size. Most statistical methods developed before the millennium were based on a linear approach even in the face of complex nature of survival data. Nonparametric nonlinear methods are best envisaged in the Machine Learning school. This book attempts to cover all these aspects in a concise way. Survival Analysis offers an integrated blend of statistical methods and machine learning useful in analysis of survival data. The purpose of the offering is to give an exposure to the machine learning trends for lifetime data analysis"--
ER  -