ISBN: 047136357X
Godina izdanja: 2002
Jezik: Engleski
Oblast: Matematika
Autor: Strani

John D. Kalbfleisch, Ross L. Prentice

Wiley 2002 439 strana

odlična očuvanost

* The Statistical Analysis of Failure Time Data
is a seminal textbook on survival analysis, authored by John D. Kalbfleisch and Ross L. Prentice. The first edition was published in 1980, followed by a second edition in 2002, and it is widely considered a benchmark text in the field.
Key Topics Covered
The book synthesizes various statistical models and methods used for analyzing failure time (or `survival`) data, focusing on regression problems, particularly in the presence of censoring. Key topics include:

Failure time models: Introduction to the core concepts and distributions used in survival analysis.
Censoring and truncation: Methods to handle data where the exact failure times are not observed (e.g., right censoring, left truncation).
Inference in parametric models: Statistical inference methods assuming specific distributions for the failure times.
Relative risk (Cox) regression models: Detailed coverage of the proportional hazards model, a cornerstone of survival analysis.
Counting processes and asymptotic theory: Advanced theoretical underpinnings using martingale convergence results.
Rank regression and the accelerated failure time (AFT) model: Alternative approaches to the proportional hazards model, focusing on the direct effect of covariates on survival time.
Competing risks and multi-state models: Analysis of scenarios where more than one type of event can occur.
Analysis of recurrent event data: Methods for data where subjects can experience the event of interest multiple times.
Analysis of correlated failure time data: Techniques for handling data where failure times within groups are related.

Significance
The book is highly regarded among graduate students, researchers, and practitioners in biostatistics, engineering, and the biomedical sciences. Its comprehensive coverage, blend of theory and application (including worked examples and problem sets), and incorporation of modern developments have established it as an essential reference in the area of survival analysis.