My thanks to Stephen Jenkins for his pointer below, I found the notes quite
detailed and helpful.
The "Discrete" entry in the [ST] Manual reads:
Discrete-time survival analysis concerns analysis of time-to-event data
whenever survival times are either
(a) intrinsically discrete (e.g. numbers of machine cycles), or
(b) grouped into discrete intervals of time ("interval censoring"). If
intervals are of equal length, then the same methods can be applied to both
(a) and (b): survival times are positive integers.
In the data set I am handling, every subject has his/her OWN interval of
time, that is their actual failure happens between two home-visit dates that
the fieldworker makes. The home-visit dates allow us to calculate the exact
ages of the subjects who fall in one of 3 categories:
i. Left-censored: the fieldworker initiates the home visits and
observes the failure has already taken place.
ii. Interval-censored: failure has take place between two home visits,
and the fieldworker has record of both dates.
iii. Right-censored: the fieldworker completes the last home visit and
failure has not been observed.
I am not sure exactly on how to structure the data to reflect the 3-states
above to use with "streg" or a similar model that would allow me to vary the
distribution of the failure time (between exponential, weibull, lognormal,
loglogistic and generalised gamma).
Great thanks for your help in advance.
Amani
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