accept_curve: (Sub-)population acceptability curves.

In bonander/CEAforests: Tree-based heterogenous cost-effectiveness and policy learning with individual-level data (beta)

Description

accept_curve Provides acceptability curves for the entire sample or for a specified subpopulation.

Usage

accept_curve(
  forest,
  from,
  to,
  length.out,
  subset = NULL,
  compare = FALSE,
  robust.se = FALSE,
  labels = NULL
)

Arguments

forest	A trained CEA forest.
from	Lowest WTP to consider.
to	Highest WTP to consider.
length.out	Number of increments from lowest to highest WTP.
subset	A specified subpopulation. See grf::average_treatment_effect for details.
compare	A logical statement. If TRUE, the subpopulation curve is compared to the sample average curve. Defaults to FALSE.
robust.se	Whether or not robust (sandwich) standard errors should be used to compute the acceptance probability. Defaults to FALSE.

Value

A matrix with acceptance probabilities given the data, subpopulation and different choices of WTP.

Examples

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bonander/CEAforests documentation built on April 1, 2021, 10:57 a.m.