| compute_EIB {BCEA} | R Documentation |
Compute Expected Incremental Benefit
Description
A summary measure useful to assess the potential changes in the decision under different scenarios.
Usage
compute_EIB(ib)
Arguments
ib |
Incremental benefit |
Details
When considering a pairwise comparison
(e.g. in the simple case of a reference intervention t = 1 and a comparator,
such as the status quo, t = 0), it is defined as the difference between the
expected utilities of the two alternatives:
eib := \mbox{E}[u(e,c;1)] - \mbox{E}[u(e,c;0)] = \mathcal{U}^1 - \mathcal{U}^0.
Analysis of the expected incremental benefit describes how the decision changes for different values of the threshold. The EIB marginalises out the uncertainty, and does not incorporate and describe explicitly the uncertainty in the outcomes. To overcome this problem the tool of choice is the CEAC.
Value
Array with dimensions (interv x k)
See Also
ceac.plot(), compute_CEAC(), compute_IB()