owsa {dampack} | R Documentation |
When used on a PSA object, this function uses a polynomial regression metamodel to predict the
average outcome of a decision-analytic model as a function of a single input parameter.
When used on a DSA object, this function uses the DSA results directly to show how the selected outcome varies
as a function of the input parameter of interest. In the DSA context, this function is called
internally by run_owsa_det
and should not be called by the user. In the PSA context,
the user must use this function to produce an owsa
object.
owsa(
sa_obj,
params = NULL,
ranges = NULL,
nsamp = 100,
outcome = c("eff", "cost", "nhb", "nmb", "nhb_loss", "nmb_loss"),
wtp = NULL,
strategies = NULL,
poly.order = 2
)
sa_obj |
sensitivity analysis object;
either a probabilistic sensitivity analysis ( |
params |
string vector with the name(s) of the parameter of interest. Defaults to all. |
ranges |
a named list of the form c("param" = c(0, 1), ...)
that gives the ranges for the parameter of interest. If NULL,
parameter values from the middle 95
from this range is determined by |
nsamp |
number of samples to take from the ranges |
outcome |
either effectiveness ("eff"), cost ("cost"), net health benefit ("nhb"), net monetary benefit ("nmb"), or the opportunity loss in terms of NHB or NMB ("nhb_loss" and "nmb_loss", respectively). "nmb_loss_voi" and "nhb_loss_voi" are only used in internal function calls of metamodel within other VOI functions. |
wtp |
if outcome is NHB or NMB (or the associated loss), must provide the willingness-to-pay threshold |
strategies |
vector of strategies to consider. The default (NULL) is that all strategies are considered. |
poly.order |
order of polynomial for the linear regression metamodel. Default: 2 |
An object of class data.frame
and owsa
with the results of the sensitivity analysis.
Can be visualized with plot.owsa, owsa_tornado, and owsa_opt_strat