  This paper presents and derives the interrelations between survival analysis
and master equation. Survival analysis deals with modeling the transitions
between succeeding states of a system in terms of hazard rates. Questions
related with this are the timing and sequencing of the states of a time series.
The frequency and characteristics of time series can be investigated by
Monte-Carlo simulations. If one is interested in cross-sectional data connected
with the stochastic process under consideration, one needs to know the temporal
evolution of the distribution of states. This can be obtained by simulation of
the associated master equation. Some new formulas allow the determination of
path-related (i.e. longitudinal) quantities like the occurence probability, the
occurence time distribution, or the effective cumulative life-time distribution
of a certain sequencing of states (path). These can be efficiently evaluated
with a recently developed simulation tool (EPIS). The effective cumulative
life-time distribution facilitates the formulation of a hidden state concept of
behavioral changes which allows an interpretation of the respective
time-dependence of hazard rates. Hidden states represent states which are
either not phenomenological distinguishable from other states, not externally
measurable, or simply not detected.
