Computes the weights to be associated with a set of competing models in order to perform structural PSA
struct.psa(models, effect, cost, ref = 1, interventions = NULL,
Kmax = 50000, plot = F)A list containing the output from either R2jags or R2OpenBUGS/R2WinBUGS for all the models that need to be combined in the model average
A list containing the measure of effectiveness computed from the various models (one matrix with n.sim x n.ints simulations for each model)
A list containing the measure of costs computed from the various models (one matrix with n.sim x n.ints simulations for each model)
Defines which intervention is considered to be the reference strategy. The default
value ref=1 means that the intervention appearing first is the reference and
the other(s) is(are) the comparator(s)
Defines the labels to be associated with each intervention. By default and
if NULL, assigns labels in the form "Intervention1", ... , "Intervention T"
Maximum value of the willingness to pay to be considered. Default value is
k=50000. The willingness to pay is then approximated on a discrete grid in
the interval [0,Kmax]. The grid is equal to wtp if the parameter is
given, or composed of 501 elements if wtp=NULL (the default)
A logical value indicating whether the function should produce the summary plot or not
Baio G. (2012). Bayesian Methods in Health Economics. CRC/Chapman Hall, London