% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/struct.psa.R
\name{struct.psa}
\alias{struct.psa}
\title{Structural Probability Sensitivity Analysis}
\usage{
struct.psa(
  models,
  effect,
  cost,
  ref = NULL,
  interventions = NULL,
  Kmax = 50000,
  plot = FALSE,
  w = NULL
)
}
\arguments{
\item{models}{A list containing the output from either R2jags or
R2WinBUGS for all the models that need to be combined in the model average}

\item{effect}{A list containing the measure of effectiveness computed from
the various models (one matrix with n.sim x n.ints simulations for each
model)}

\item{cost}{A list containing the measure of costs computed from the various
models (one matrix with n.sim x n.ints simulations for each model)}

\item{ref}{Which intervention is considered to be the reference
strategy. The default value \code{ref=1} means that the intervention
appearing first is the reference and the other(s) is(are) the comparator(s)}

\item{interventions}{Defines the labels to be associated with each
intervention. By default and if \code{NULL}, assigns labels in the form
"Intervention1", ... , "InterventionT"}

\item{Kmax}{Maximum value of the willingness to pay to be considered.
Default value is \code{50000}. The willingness to pay is then approximated
on a discrete grid in the interval \verb{[0, Kmax]}. The grid is equal to
\code{k} if the parameter is given, or composed of \code{501} elements if
\code{k=NULL} (the default)}

\item{plot}{A logical value indicating whether the function should produce
the summary plot or not}

\item{w}{A vector of weights. By default it's NULL to indicate that the
function will calculate the model weights based on DIC and the individual
model fit. This behaviour can be overridden by passing a vector \code{w},
for instance based on expert opinion}
}
\value{
List object of bcea object, model weights and DIC
}
\description{
Computes the weights to be associated with a set of competing models in
order to perform structural PSA.
}
\details{
The model is a list containing the output from either R2jags or
R2WinBUGS for all the models that need to be combined in the model average
effect is a list containing the measure of effectiveness computed from the
various models (one matrix with n_sim x n_ints simulations for each model)
cost is a list containing the measure of costs computed from the various
models (one matrix with n_sim x n_ints simulations for each model).
}
\examples{

\dontrun{
# load sample jags output
load(system.file("extdata", "statins_base.RData", package = "BCEA"))
load(system.file("extdata", "statins_HC.RData", package = "BCEA"))

interventions <- c("Atorvastatin", "Fluvastatin",
                   "Lovastatin", "Pravastatin",
                   "Rosuvastatin", "Simvastatin")

m1 <- bcea(eff = statins_base$sims.list$effect,
           cost = statins_base$sims.list$cost.tot,
           ref = 1, interventions = interventions)

m2 <- bcea(eff = statins_HC$sims.list$effect,
           cost = statins_HC$sims.list$cost.tot,
           ref = 1, interventions = interventions)

models <- list(statins_base, statins_HC)

effects <- list(statins_base$sims.list$effect,
                statins_HC$sims.list$effect)
costs <- list(statins_base$sims.list$cost.tot,
              statins_HC$sims.list$cost.tot)

m3 <- struct.psa(models, effects, costs,
                 ref = 1, interventions = interventions)
}

}
\references{
\insertRef{Baio2013}{BCEA}
}
\seealso{
\code{\link[=bcea]{bcea()}}
}
\author{
Gianluca Baio
}
