compute_EIB: Compute Expected Incremental Benefit

View source: R/compute_xxx.R

compute_EIBR 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()


BCEA documentation built on Nov. 25, 2023, 5:08 p.m.