ICEwedge {ICEinfer} | R Documentation |
Equivariant Wedge-Shaped ICE Region with Confidence Level from 0.50 to 0.99
Description
ICEwedge() uses the Bootstrap Distribution of ICE Uncertainty generated by ICEuncrt() to calculate and sort ICE Angle Order Statistics around a circle. ICEwedge() then counts outwards the same number of ICE Angle Order Statistics, floor(R*conf/2), both Counter-Clockwise and Clockwise from the so-called "center" Order Statistic (the one nearest to the Observed ICE Ratio) to define a pair of ICE Ray Endpoints at ICE Angle Order Statistics (reported as numbers jlo and kup, respectively) that subtend an ICE Polar Angle reported in degrees.
Usage
ICEwedge(ICEu, lfact = 1, conf = 0.95)
Arguments
ICEu |
Output list object of class ICEuncrt. |
lfact |
Either a strictly positive multiplicative factor for ICEu item lambda or else 0 to cause ICEwedge to compute the positive lfact and lambda values that transform the alibi display to have an alias interpretation. |
conf |
Statistical Confidence Level within [0.50, 0.99]. |
Details
The plot() of an object of class ICEwedge displays the Bootstrap Distribution of ICE Uncertainty with a small, circular, colored dot (pch = 20). Outcomes outside the Wedge are displayed in black, while outcomes inside the Wedge are displayed in cyan. Upper and lower ICE Ray Limits are displayed as solid black lines, and the ICE Ray through the center ICE Angle Order Statistic is shown as a dashed black line.
Value
An object of class ICEwedge with the following output list:
ICEinp |
Name of the ICEuncrt object input to ICEwedge(). |
lambda |
Positive value of lfact * ICEu item lambda |
lfact |
Positive Multiplier for the ICEu item lambda value input to ICEwedge(). |
unit |
Saved value of unit, cost or effe, input to ICEuncrt. |
conf |
Statistical Confidence Level within [0.50, 0.99] input to ICEwedge. |
R |
Saved integer value for number of bootstrap replications input to ICEuncrt. |
axys |
R x 4 data.frame with ICE Angle in column 1, bootstrap resampled values of (DeltaEffe, DeltaCost) in columns 2 and 3, and the binary flag with 0 => outcome outSide the Confidence Wedge and 1 => outcome inSide the Confidence Wedge in column 4. |
t1 |
Observed value of (DeltaEffe, DeltaCost) when each patient is sampled exactly once. |
ia1 |
The center ICE Angle closest to the Objerved ICE Ratio. |
center |
The largest value of j such that axys[j, 1] < ia1 <= axys[j+1, 1]. |
jlo |
Number of the ICE Angle Order Statistic defining the Clockwise or lower ICE Ray boundary of the Confidence Wedge. |
kup |
Number of the ICE Angle Order Statistic defining the Counter-Clockwise or upper ICE Ray boundary of the Confidence Wedge. |
subangle |
Subtended Polar ICE Angle between Order Statistics numbers jlo and kup. |
xmax |
Alias plots of ICEwedge have horizontal range [-xmax, +xmax]. |
ymax |
Alias plots of ICEwedge have vertical range [-ymax, +ymax]. |
ab |
ICE angle computation perspective of alibi or alias. |
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. Resampling and multiplicity in cost-effectiveness inference. Journal of Biopharmaceutical Statistics 1999; 9(4): 563-582.
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.
See Also
Examples
data(dpunc)
# ICEwedge() calculations may take more than 5 seconds...
dpwdg <- ICEwedge(dpunc)
plot(dpwdg)
# ICEwedge() computations from an alias (rather than alibi) perspective...
dpwdg0 <- ICEwedge(dpunc, lfact=0)
plot(dpwdg0)