struct.psa {BCEA} | R Documentation |
Structural Probability Sensitivity Analysis
Description
Computes the weights to be associated with a set of competing models in order to perform structural PSA.
Usage
struct.psa(
models,
effect,
cost,
ref = NULL,
interventions = NULL,
Kmax = 50000,
plot = FALSE,
w = NULL
)
Arguments
models |
A (possibly named) list containing the output from either R2jags or R2WinBUGS for all the models that need to be combined in the model average |
effect |
A list containing the measure of effectiveness computed from
the various models (one matrix with |
cost |
A list containing the measure of costs computed from the various
models (one matrix with |
ref |
Which intervention is considered to be the reference
strategy. The default value |
interventions |
Defines the labels to be associated with each
intervention. By default and if |
Kmax |
Maximum value of the willingness to pay to be considered.
Default value is |
plot |
A logical value indicating whether the function should produce the summary plot or not |
w |
A vector of weights. By default it's |
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).
Value
List object of bcea object, model weights and DIC
Author(s)
Gianluca Baio
References
Baio G (2013). Bayesian Methods in Health Economics. CRC.
See Also
Examples
# load sample jags output
data("statins_base")
data("statins_HC")
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("Base"=statins_base, "Half Cauchy"=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)
## Not run:
m3 <- struct.psa(models, effects, costs,
ref = 1, interventions = interventions)
## End(Not run)