An object of class survival stores survival probabilities. It is typically
returned by Psm$sim_survival() or PsmCurves$survival(); however, it can also
be constructed "manually" from existing data using the survival()
function as described below. The latter option is useful if survival modeling
has been performed by an R package other than those that integrate with hesim (
currently flexsurv). In this case a simulation model can still be developed
by using sim_stateprobs.survival() to compute simulated state probabilities and
then simulating quality-adjusted life-years and costs in a typical fashion.
survival(
data,
sample = "sample",
strategy_id = "strategy_id",
patient_id = "patient_id",
grp_id = "grp_id",
curve = "curve",
t = "t",
survival = "survival"
)An object of class survival that inherits from data.table and contains
the following columns:
A random sample from the PSA.
The treatment strategy ID.
The patient ID.
The subgroup ID.
One of the N-1 survival curves in an N-state partitioned
survival model. Each curve corresponds to unique endpoint.
The time at which a survival probability is computed.
The probability of surviving to time t.
The object also contains a size attribute that contains the elements
n_samples, n_strategies, n_patients, n_states, and n_times denoting
the number of samples, treatment strategies, patients, health states, and times.
A tabular object that can be coerced to a data.table with
as.data.table().
The name of the column corresponding to sample.
The name of the column corresponding to strategy_id.
The name of the column corresponding to patient_id.
The name of the column corresponding to grp_id.
The name of the column corresponding to curve.
The name of the column corresponding to t.
The name of the column corresponding to survival.
survival objects are returned by methods in the Psm and PsmCurves
classes. An example in which a survival object is constructed "manually"
(presumably from a preexisting survival model fit using software other than flexsurv)
is provided in the documentation to sim_stateprobs.survival().