Create a table for storing parameter estimates used to simulate costs or utility in an economic model by treatment strategy, patient, health state, and (optionally) time interval.
stateval_tbl(
tbl,
dist = c("norm", "beta", "gamma", "lnorm", "unif", "fixed", "custom"),
hesim_data = NULL,
grp_var = NULL
)A data.frame or data.table for storing parameter
values. See "Details" for specifics.
Probability distribution used to sample parameters for a probabilistic sensitivity analysis (PSA).
A hesim_data object. This argument is deprecated
and should be passed to create_StateVals.stateval_tbl() instead.
The name of the variable used to group patients.
An object of class stateval_tbl, which is a data.table of
parameter values with attributes for dist and grp_var.
tbl is a tabular object containing columns for treatment
strategies (strategy_id), patients (patient_id),
health states (state_id), and/or the start of time intervals
(time_start). The table must contain at least one column
named strategy_id, patient_id, or state_id,
but does not need to contain all of them. Each row denotes a unique
treatment strategy, patient, health state, and/or time interval pair.
tbl may also contain a column with the name specified in grp_var
(rather than patient_id) so that state values are assigned to
groups of patients.
tbl must also contain columns summarizing the state values for each
row, which depend on the probability distribution selected with dist.
Available distributions include the normal (norm), beta (beta),
gamma (gamma), lognormal (lnorm), and uniform (unif)
distributions. In addition, the option fixed can be used if estimates
are known with certainty and custom can be used if
parameter values for a PSA have been previously
sampled from an arbitrary probability distribution.
The columns in tbl that must be included,
by distribution, are:
mean and sd
mean and se or shape1 and shape2
mean and se, shape and rate,
or shape and scale
meanlog or sdlog
min and max
est
sample and value
Note that if dist = "custom", then tbl must include a column
named sample (an integer vector denoting a unique random draw) and
value (denoting the value of the randomly sampled parameter). In this case,
there is a unique row in tbl for each random draw (sample) and
each combination of strategies, patients, health states, and/or time intervals.
Again, tbl must contain at least one column
named strategy_id, patient_id (or grp_var), or state_id,
but does not need to contain them all.
strategies <- data.frame(strategy_id = c(1, 2))
patients <- data.frame(patient_id = seq(1, 3),
grp = c(1, 1, 2),
age = c(45, 50, 60),
female = c(0, 0, 1))
states <- data.frame(state_id = c(1, 2))
hesim_dat <- hesim_data(strategies = strategies,
patients = patients,
states = states)
# Utility varies by health state and patient group
utility_tbl <- stateval_tbl(data.frame(state_id = rep(states$state_id, 2),
grp = rep(rep(c(1, 2)), each = nrow(states)),
mean = c(.8, .7, .75, .55),
se = c(.18, .12, .10, .06)),
dist = "beta",
grp_var = "grp")
print(utility_tbl)
#> grp state_id mean se
#> 1: 1 1 0.80 0.18
#> 2: 1 2 0.70 0.12
#> 3: 2 1 0.75 0.10
#> 4: 2 2 0.55 0.06
utilmod <- create_StateVals(utility_tbl, n = 2, hesim_data = hesim_dat)
# Costs vary by treatment strategy
cost_tbl <- stateval_tbl(data.frame(strategy_id = strategies$strategy_id,
mean = c(5000, 3000),
se = c(200, 100)),
dist = "gamma")
print(cost_tbl)
#> strategy_id mean se
#> 1: 1 5000 200
#> 2: 2 3000 100
costmod <- create_StateVals(cost_tbl, n = 2, hesim_data = hesim_dat)