Article,
Survival analysis part II: multivariate data analysis--an introduction to concepts and methods
Br J Cancer, 89 (3): 431-436 (August 2003)
DOI: 10.1038/sj.bjc.6601119
Abstract
Survival analysis involves the consideration of the time between a
fixed starting point (e.g. diagnosis of cancer) and a terminating
event (e.g. death). The key feature that distinguishes such data
from other types is that the event will not necessarily have
occurred in all individuals by the time the study ends, and for
these patients, their full survival times are unknown. For instance,
in studies that measure the length of survival after diagnosis of
cancer, it is common for a proportion of individuals to remain
alive and disease-free at the end of the follow-up period, and for
these patients, we know only a lower limit on their actual time to
event. Thus, special methods are required for these type of data.
The explanation and demonstration of some of the methods
proposed to analyse such data are the basis of this series.
In the first paper of this series (Clark et al, 2003), we described
initial methods for analysing and summarising survival data
including the definition of hazard and survival functions, and
testing for a difference between two groups. We continue here by
considering various statistical models and, in particular, how to
estimate the effect of one or more factors that may predict survival.
