ICEcolor {ICEinfer}R Documentation

Compute Preference Colors for Outcomes in a Bootstrap ICE Scatter within a Confidence Wedge

Description

Assuming ICEw is an object of class ICEwedge, ICEcolor uses the value of lambda given by lfact * (ICEw item lambda) and the ICE Preference Map with parameters beta and gamma to compute the Economic Preference value for only the points in a Bootstrap Distribution of ICE Uncertainty that also happen to fall within the ICE confidence wedge. When the overall level of confidence (statistical size of the wedge) is held fixed, the points to be colored are always the very same points for all choices of lambda. However, the numerical value of preference (and thus the color) for each such point as well as potential overall asymmetry in the resulting ICE map do depend greatly upon choice of lambda.

Usage

 ICEcolor(ICEw, lfact = 1, beta = 1, gamma = 3+2*sqrt(2)) 

Arguments

ICEw Existing ICEwedge object.
lfact Strictly positive multiplier for ICEw item lambda.
beta Strictly positive Returns-to-Scale power parameter for the ICE Preference Map. beta = 1 implies linear (constant) Returns to Scale. beta > 0 and < 1 implies diminishing Returns to Scale. beta > 1 implies increasing Returns to Scale.
gamma Strictly positive Directional power parameter. The smallest reasonable value for gamma is usually gamma = beta, which yields a (generalized) linear map. The largest reasonable value for gamma is usually gamma = beta*(3+2*sgrt(2)), which yields a map that satisfies the Cartesian Monotonicity Axiom and also admits all possible finite values for WTP and WTA, i.e. all values greater than or equal to 0 but less than +Inf.

Details

Multiple calls to ICEcolor() are usually made for different lfact multipliers of the lambda item within ICEw as well as different choices for the ICE Preference power parameters, beta and gamma. Calls to plot(x, alibi) for these alternative ICEcolor x-objects can be used to illustrate that exogenous Economic Uncertainty can literally SWAMP the Statistical Uncertainty endogenous to patient level data on the relative cost and effectiveness of two treatments.

Value

Object of class ICEcolor containing an output list with the following items:

df Saved value of the name of the data.frame input to ICEcolor.
lambda Saved positive value of lambda input to ICEcolor.
unit Saved value of unit, cost or effe, input to ICEcolor.
R Saved integer value for number of bootstrap replications input to ICEcolor.
trtm Saved name of the treatment indicator within the df data.frame.
xeffe Saved name of the treatment effectiveness variable within the df data.frame.
ycost Saved name of the treatment cost variable within the df data.frame.
effcst Saved value of the sorted 3-variable (trtm,effe,cost) data.frame.
t1 Observed value of (DeltaEffe, DeltaCost) when each patient is sampled exactly once.
t R x 2 matrix of values of (DeltaEffe, DeltaCost) computed from bootstrap resamples.
seed Saved value of the seed used to start pseudo random number generation.

Author(s)

Bob Obenchain <wizbob@att.net>

References

Cook JR, Heyse JF. Use of an angular transformation for ratio estimation in cost-effectiveness analysis. Statistics in Medicine 2000; 19: 2989-3003.

Obenchain RL. ICE Preference Maps: Nonlinear Generalizations of Net Benefit and Acceptability. Health Serv Outcomes Res Method 2008; 8: 31-56. DOI 10.1007/s10742-007-0027-2. Open Access.

Obenchain RL. ICEinR.pdf ../R_HOME/library/ICEinfer 2009; 30 pages.

See Also

ICEwedge, plot.ICEcolor and print.ICEcolor

Examples

  # Read in previously computed ICEwedge output list.
  data(dpwdg)
  dpcol <- ICEcolor(dpwdg)
  # Display preference coloring for the stored value of lambda.
  plot(dpcol)
  dpcolX <- ICEcolor(dpwdg, lfact=10)
  # Display preference coloring when lambda is increased by a factor of 10.
  plot(dpcolX)

[Package ICEinfer version 0.2-0 Index]