ICEepmap {ICEinfer} | R Documentation |
ICEepmap() and ICEomega() define ICE Preference Map Parameter Values by defining an object, pm, of class ICEepmap for display using print(pm) or plot(pm, xygrid).
ICEepmap(lambda = 1, beta = 1, gamma = 3 + 2 * sqrt(2)) ICEomega(lambda = 1, beta = 1, eta = 3 + 2 * sqrt(2))
lambda |
Optional; Positive value for the Shadow Price of Health. |
beta |
Optional; Positive Returns-to-Scale Power parameter for the ICE Preference Map. beta = 1 implies linear (constant) Returns to Scale. A beta > 0 and < 1 implies diminishing Returns to Scale. A beta > 1 implies increasing Returns to Scale. |
gamma |
Optional for ICEepmap(); 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 Cartesian Monotonicity and also yields WTP and WTA values within [0, +Inf). |
eta |
Optional for ICEomega(); Positive Power Parameter Ratio. Generalized linear maps result when eta = 1. The eta for the more realistic Nonlinear maps is greater than one, but not greater than the Omega limit of (3+2*sgrt(2)), which is approximately 5.828. This upper limit on eta is required for Cartesian Monotonicity to hold. |
The ICEepmap() and ICEomega() functions specify numerical values for the Shadow Price of Health Parameter, lambda, for the Returns to Scale Power Parameter, beta, and for either the Directional Power Parameter, gamma, or else the Power Parameter Ratio, eta = gamma / beta.
Object of class ICEepmap containing an output list with the following items:
lambda |
Saved positive value of Shadow Price of Health, lambda, read by the print and plot methods for objects of class ICEepmap. |
beta |
Saved Positive Returns-to-Scale Power parameter, beta, read by the print and plot methods for objects of class ICEepmap. |
gamma |
Saved Positive Directional Power parameter, gamma, read by the print and plot methods for objects of class ICEepmap. |
Bob Obenchain <softrx@iquest.net>
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. Incremental Cost-Effectiveness (ICE) Preference Maps. 2001 JSM Proceedings (Biopharmaceutical Section) on CD-ROM. (10 pages.) Alexandria, VA: American Statistical Association. 2002.
Obenchain RL. ICE Preference Maps: Nonlinear Generalizations of Net Benefit and Acceptability. Lilly US Health Outcomes White Paper. 2007; 52 pages.
Obenchain RL. ICEinR.pdf ../R_HOME/library/ICEinfer 2007; 30 pages.
plot.ICEepmap
and print.ICEepmap
pm <- ICEomega(beta=0.8) require(lattice) plot(pm)