ceac: Cost-Effectiveness Acceptability Curves

In uo-cmor/cea: Functions for Trial-Based Cost-Effectiveness Analysis

Description

Generate a cost-effectiveness acceptability curve (CEAC) from a fitted CEA regression model.

Usage

ceac(x, wtp_max, wtp_step, QALYs = "QALYs", Costs = "Costs", ...)

## S3 method for class 'cea_estimate'
ceac(
  x,
  wtp_max,
  wtp_step,
  QALYs = "QALYs",
  Costs = "Costs",
  estimand = "ATE",
  method = "delta",
  R,
  sim = "parametric",
  ...
)

## S3 method for class 'cea_boot'
ceac(x, wtp_max, wtp_step, QALYs = "QALYs", Costs = "Costs", ...)

Arguments

x	cea_estimate or cea_boot object. The fitted CEA regression model or bootstrap resampling from the fitted model.
wtp_max	Maximum willingness-to-pay level for calculation.
wtp_step	Interval between calculated willingness-to-pay levels.
QALYs, Costs	Names of the variables in x representing QALYs and Costs, respectively.
...	Passed to boot_cea.
estimand	String scalar. Whether to calculate the average treatment effect (ATE), average treatment effect on the treated (ATT), or average treatment effect on the controls (ATC). Only used for non-linear models.
method	Which method to use. Currently only 'boot' (bootstrap) is implemented.
R	The number of bootstrap replicates.
sim	A character vector indicating the type of simulation required. Possible values are "ordinary" (the default), "parametric", "balanced", or "permutation".

uo-cmor/cea documentation built on Dec. 23, 2021, 2:01 p.m.