Survival Analysis
Lawrence M. Friedman,
Curt D. Furberg,
David L. DeMets,
David M. Reboussin and
Christopher B. Granger
Additional contact information
Curt D. Furberg: Wake Forest School of Medicine, Division of Public Health Sciences
David L. DeMets: University of Wisconsin, Department Biostatistics and Medical Informatics
David M. Reboussin: Wake Forest School of Medicine, Department of Biostatistics
Christopher B. Granger: Duke University, Department of Medicine
Chapter Chapter 15 in Fundamentals of Clinical Trials, 2015, pp 319-341 from Springer
Abstract:
Abstract This chapter reviews some of the fundamental concepts and basic methods in survival analysis. Frequently, event rates such as mortality or occurrence of nonfatal myocardial infarction are selected as primary response variables. The analysis of such event rates in two groups could employ the chi-square statistic or the equivalent normal statistic for the comparison of two proportions. However, when the length of observation is different for each participant, estimating an event rate is more complicated. Furthermore, simple comparison of event rates between two groups is not necessarily the most informative type of analysis. For example, the 5-year survival for two groups may be nearly identical, but the survival rates may be quite different at various times during the 5 years. This is illustrated by the survival curves in Fig. 15.1. This figure shows survival probability on the vertical axis and time on the horizontal axis. For Group A, the survival rate (or one minus the mortality rate) declines steadily over the 5 years of observation. For Group B, however, the decline in the survival rate is rapid during the first year and then levels off. Obviously, the survival experience of the two groups is not the same, although the mortality rate at 5 years is nearly the same. If only the 5-year survival rate is considered, Group A and Group B appear equivalent. Curves such as these might reasonably be expected in a trial of surgical versus medical intervention, where surgery might carry a high initial operative mortality.
Date: 2015
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-18539-2_15
Ordering information: This item can be ordered from
http://www.springer.com/9783319185392
DOI: 10.1007/978-3-319-18539-2_15
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().