Survival Analysis for Epidemiologic and Medical Research

Informationen zum Autor Steve Selvin is Professor of Biostatistics and Epidemiology at the University of California, Berkeley. He has taught on the Berkeley campus for 35 years and has authored or co-authored more than 200 scientific articles in the areas of applied statistics and epidemiology. He has received two university teaching awards and is a member of the ASPH/Pfizer Public Health Academy of Distinguished Teachers. Klappentext For readers with a minimal background in statistics, this text shows how to analyze and interpret epidemiological and medical survival data. Zusammenfassung This practical guide for readers with a minimal background in statistics shows how to analyze and interpret epidemiologic and medical survival data with the help of modern computer systems. The author introduces key methods of survival analysis that are also central to statistical analysis in general. Inhaltsverzeichnis 1. Rates and their properties; 2. Life tables; 3. Two especially useful estimation tools; 4. Product-limit estimation; 5. Exponential survival time probability distribution; 6. Weibull survival time probability distribution; 7. Analysis of two-sample survival data; 8. General hazards model: parametric; 9. General hazards model: nonparametric.

Klappentext
For readers with a minimal background in statistics, this text shows how to analyze and interpret epidemiological and medical survival data.

Zusammenfassung
This practical guide for readers with a minimal background in statistics shows how to analyze and interpret epidemiologic and medical survival data with the help of modern computer systems. The author introduces key methods of survival analysis that are also central to statistical analysis in general.

Inhalt
1. Rates and their properties; 2. Life tables; 3. Two especially useful estimation tools; 4. Product-limit estimation; 5. Exponential survival time probability distribution; 6. Weibull survival time probability distribution; 7. Analysis of two-sample survival data; 8. General hazards model: parametric; 9. General hazards model: nonparametric.

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