% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/info.rank.R
\name{info.rank.bcea}
\alias{info.rank.bcea}
\alias{info.rank}
\title{Information-Rank Plot for bcea Class}
\usage{
\method{info.rank}{bcea}(
  he,
  inp,
  wtp = NULL,
  howManyPars = NA,
  graph = c("base", "ggplot2", "plotly"),
  rel = TRUE,
  ...
)

info.rank(he, ...)
}
\arguments{
\item{he}{A \code{bcea} object containing the results of the Bayesian
modelling and the economic evaluation.}

\item{inp}{Named list from running \code{createInputs()} containing:
\itemize{
\item \code{parameter} = A vector of parameters for which the individual EVPPI
should be calculated. This can be given as a string (or vector of strings)
of names or a numeric vector, corresponding to the column numbers of
important parameters.
\item \code{mat} = A matrix containing the simulations for all the parameters
monitored by the call to JAGS or BUGS. The matrix should have column names
matching the names of the parameters and the values in the vector parameter
should match at least one of those values.
}}

\item{wtp}{A value of the wtp for which the analysis should be performed. If
not specified then the break-even point for the current model will be used.}

\item{howManyPars}{Optional maximum number of parameters to be included in the bar plot.
Includes all parameters by default.}

\item{graph}{A string used to select the graphical engine to use for plotting.
Should (partial-)match one of the two options "base" or "plotly". Default value is "base"}

\item{rel}{Logical argument that specifies whether the ratio of
EVPPI to EVPI (\code{rel = TRUE}, default) or the absolute value of the EVPPI
should be used for the analysis.}

\item{...}{Additional options. These include graphical parameters that the
user can specify:
\itemize{
\item \code{xlim} = limits of the x-axis; ca = font size for the axis
label (default = 0.7 of full size).
\item \code{cn} = font size for the parameter names
vector (default = 0.7 of full size) - base graphics only.
\item \code{mai} = margins of the graph (default = c(1.36, 1.5, 1,1)) - base graphics only.
}}
}
\value{
With base graphics: A data.frame containing the ranking of the parameters
with the value of the selected summary, for the chosen wtp; with plotly: a plotly object,
incorporating in the $rank element the data.frame as above.
The function produces a 'Info-rank' plot. This is an extension of standard 'Tornado
plots' and presents a ranking of the model parameters in terms of their
impact on the expected value of information. For each parameter, the
specific individual EVPPI is computed and used to measure the impact of
uncertainty in that parameter over the decision-making process, in terms of
how large the expected value of gaining more information is.
}
\description{
Produces a plot similar to a tornado plot, but based on the analysis of the
EVPPI. For each parameter and value of the willingness-to-pay threshold, a
barchart is plotted to describe the ratio of EVPPI (specific to that
parameter) to EVPI. This represents the relative `importance' of each
parameter in terms of the expected value of information.
}
\examples{
\dontrun{
# Load the post-processed results of the MCMC simulation model
# original JAGS output is can be downloaded from here
# https://gianluca.statistica.it/book/bcea/code/vaccine.RData

data("Vaccine")
m <- bcea(eff, cost)
inp <- createInputs(vaccine_mat)
info.rank(m, inp)

info.rank(m, inp, graph = "base")
info.rank(m, inp, graph = "plotly")
info.rank(m, inp, graph = "ggplot2")
}

}
\references{
\insertRef{Baio2011}{BCEA}

\insertRef{Baio2013}{BCEA}
}
\seealso{
\code{\link[=bcea]{bcea()}},
\code{\link[=evppi]{evppi()}}
}
\author{
Anna Heath, Gianluca Baio, Andrea Berardi
}
\keyword{dplot}
\keyword{models}
