Simulate values (i.e., utility or costs) associated with health states in a state transition or partitioned survival model.
paramsParameters for simulating state values. Currently supports
objects of class tparams_mean or params_lm.
input_dataAn object of class input_mats. Only used for
params_lm objects.
methodThe method used to simulate costs and
quality-adjusted life-years (QALYs) as a function of state values.
If wlos, then costs and QALYs are
simulated by weighting state values by the length of stay in a health
state. If starting, then state values represent a one-time value
that occurs when a patient enters a health state. When starting is
used in a cohort model, the state values only accrue at time 0;
in contrast, in an individual-level model, state values
accrue each time a patient enters a new state and are discounted based on
time of entrance into that state.
time_resetIf FALSE then time intervals are based on time since
the start of the simulation. If TRUE, then time intervals reset each
time a patient enters a new health state. This is relevant if, for example,
costs vary over time within health states. Only used if method = wlos.
new()Create a new StateVals object.
StateVals$new(
params,
input_data = NULL,
method = c("wlos", "starting"),
time_reset = FALSE
)paramsThe params field.
input_dataThe input_data field.
methodThe method field.
time_resetThe time_reset field.
A new StateVals object.
sim()Simulate state values with either predicted means or random samples by
treatment strategy, patient, health state, and time t.
StateVals$sim(t, type = c("predict", "random"))tA numeric vector of times.
type"predict" for mean values or "random" for random samples.
A data.table of simulated state values with columns for sample,
strategy_id, patient_id, state_id, time, and value.
check()Input validation for class. Checks that fields are the correct type.
StateVals$check()
clone()The objects of this class are cloneable with this method.
StateVals$clone(deep = FALSE)
deepWhether to make a deep clone.