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Survival Analysis A Self-Learning Text, Third Edition /
This greatly expanded third 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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York, NY :
Springer New York : Imprint: Springer,
2012.
|
| Edición: | 3rd ed. 2012. |
| Colección: | Statistics for Biology and Health,
|
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 100 | 1 | |a Kleinbaum, David G. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Survival Analysis |h [electronic resource] : |b A Self-Learning Text, Third Edition / |c by David G. Kleinbaum, Mitchel Klein. |
| 250 | |a 3rd ed. 2012. | ||
| 264 | 1 | |a New York, NY : |b Springer New York : |b Imprint: Springer, |c 2012. | |
| 300 | |a XV, 700 p. 500 illus. |b online resource. | ||
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| 490 | 1 | |a Statistics for Biology and Health, |x 2197-5671 | |
| 505 | 0 | |a Introduction to Survival Analysis -- Kaplan-Meier Survival Curves and the Log-Rank Test -- The Cox Proportional Hazards Model and Its Characteristics -- Evaluating the Proportional Hazards Assumption -- The Stratified Cox Procedure -- Extension of the Cox Proportional Hazards Model for Time-Dependent Variables -- Parametric Survival Models.- Recurrent Events Survival Analysis -- Competing Risks Survival Analysis. | |
| 520 | |a This greatly expanded third 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 third edition continues to use the unique "lecture-book" format of the first two editions with one new chapter, additional sections and clarifications to several chapters, and a revised computer appendix. The Computer Appendix, with step-by-step instructions for using the computer packages STATA, SAS, and SPSS, is expanded to include the software package R. 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. | ||
| 650 | 0 | |a Biometry. | |
| 650 | 0 | |a Epidemiology. | |
| 650 | 1 | 4 | |a Biostatistics. |
| 650 | 2 | 4 | |a Epidemiology. |
| 700 | 1 | |a Klein, Mitchel. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
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| 830 | 0 | |a Statistics for Biology and Health, |x 2197-5671 | |
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