 |
Survival Analysis: A Self-Learning Text (Statistics for Biology and Health)
Be the First to Write a Review and tell the world about this title!Books on similar topics, in best-seller order: Books from the same publisher, in best-seller order:
This greatly expanded second edition of Survival Analysis- A Self-learning
Text provides a highly readable description of state-of-the-art methods of analysis
of survival/event-history data. This text is suitable for researchers and statisticians
working in the medical and other life sciences as well as statisticians in academia
who teach introductory and second-level courses on survival analysis. The second
edition continues to use the unique "lecture-book" format of the first (1996)
edition with the addition of three new chapters on advanced topics:
Chapter 7: Parametric Models
Chapter 8: Recurrent events
Chapter 9: Competing Risks.
Also, the Computer Appendix has been revised to provide step-by-step instructions
for using the computer packages STATA (Version 7.0), SAS (Version 8.2), and
SPSS (version 11.5) to carry out the procedures presented in the main text.
The original six chapters have been modified slightly
to expand and clarify aspects of survival analysis in response to suggestions
by students, colleagues and reviewers, and
to add theoretical background, particularly regarding the formulation of
the (partial) likelihood functions for proportional hazards, stratified, and
extended Cox regression models
About the Authors:
David Kleinbaum is Professor of Epidemiology at the Rollins School of Public
Health at Emory University, Atlanta, Georgia. Dr. Kleinbaum is internationally
known for innovative textbooks and teaching on epidemiological methods, multiple
linear regression, logistic regression, and survival analysis. He has provided
extensive worldwide short-course training in over 150 short courses on statistical
and epidemiological methods. He is also the author of ActivEpi (2002), an interactive
computer-based instructional text on fundamentals of epidemiology, which has
been used in a variety of educational environments including distance learning.
Mitchel Klein is Research Assistant Professor with a joint appointment in the
Department of Environmental and Occupational Health (EOH) and the Department
of Epidemiology, also at the Rollins School of Public Health at Emory University.
Dr. Klein is also co-author with Dr. Kleinbaum of the second edition of Logistic
Regression- A Self-Learning Text (2002). He has regularly taught epidemiologic
methods courses at Emory to graduate students in public health and in clinical
medicine. He is responsible for the epidemiologic methods training of physicians
enrolled in Emory’s Master of Science in Clinical Research Program, and has
collaborated with Dr. Kleinbaum both nationally and internationally in teaching
several short courses on various topics in epidemiologic methods.
|
|
