R: ICEscale() functions compute or print ICE Statistical...
ICEscale
R Documentation
ICEscale() functions compute or print ICE Statistical Inference Summary Statistics
relative to choice for the numerical value of the Shadow Price of Health, lambda
Description
ICEscale() computes Summary Statistics for 2-sample, 2-variable inference where one variable
is a measure of effectiveness (higher values are better) and the other variable is a measure
of cost (lower values are better). The 2 samples are of patients receiving only 1 of the 2
possible treatments. The treatment called new is the one with the higher numerical level
for the specified treatment indicator variable, while the treatment called std corresponds
to the lower numerical level. The pivotal statistic for inference is (DeltaEffe, DeltaCost),
which are the head-to-head mean differences for new treatment minus std treatment. Each
sample is assumed to provide unbiased estimates of the overall expected effectiveness and cost
for that treatment.
Usage
ICEscale(df, trtm, xeffe, ycost, lambda = 1, unit = cost)
Arguments
df
Required; Existing data.frame object containing the trtm, xeffe and ycost variables.
trtm
Required; Name of the treatment indicator variable contained within the df
data.frame that assumes one of only two different numerical values for each patient.
xeffe
Required; Name of the treatment effectiveness variable within the df data.frame.
ycost
Required; Name of the treatment cost variable within the df data.frame.
lambda
Optional; lambda strictly positive value for the Shadow Price of Health.
unit
Optional; unit character string containing either cost (default) or effe.
Details
After an initial call with the default value of lambda = 1, multiple additional calls to
ICEscale() with different numerical values for lambda are usually made at the very beginning of
analyses using other functions from the ICEinfer package. For example, the statistical
choice for lambda assures that the DeltaEffe and DeltaCost mean treatment differences (new
minus std) will have approximately equal variability when expressed in either cost or
effe units. The power of ten value of lambda that is closest to the statistical value
for lambda assures use of units that, except for the position of the decimal point, are identical
to the cost/effectiveness ratio implied by the scales in which data values are stored within
the input data.frame.
Value
Object of class ICEscale containing an output list with the following items:
trtm
Saved name of the treatment indicator within the input data.frame.
xeffe
Saved name of the treatment effectiveness variable within the input data.frame.
ycost
Saved name of the treatment cost variable within the input data.frame.
effcst
Saved value of the sorted 3-variable (trtm,effe,cost) data.frame.
lambda
Value for the Shadow Price of Health, lambda, input to ICEscals().
t1
Observed values of (DeltaEffe, DeltaCost) when each distinct patient is sampled
exactly once.
s1
Observed values for the standard deviations of (DeltaEffe, DeltaCost) when each
distinct patient is sampled exactly once.
slam
Statistical Shadow Price computed as s1[2]/s1[1] and rounded to digits = 3.
potlam
Power-of-Ten Shadow Price computed as 10^(as.integer(log10(slam))).
Author(s)
Bob Obenchain <wizbob@att.net>
References
Obenchain RL. Issues and algorithms in cost-effectiveness inference. Biopharmaceutical
Reports 1997; 5(2): 1-7. Washington, DC: American Statistical Association.
Obenchain RL. ICEplane: a windows application for incremental cost-effectiveness (ICE)
statistical inference. Copyright (c) Pharmaceutical Research and Manufacturers of America
(PhRMA.) http://www.math.iupui.edu/~indyasa/bobodown.htm 1997–2007.
Obenchain RL. ICEinR.pdf Vignette-like documentation for ICEinfer
stored in the R library/ICEinfer/doc folder. 2009; 30 pages.
Cook JR, Heyse JF. Use of an angular transformation for ratio estimation in cost-effectiveness
analysis. Statistics in Medicine 2000; 19: 2989-3003.
See Also
ICEscale, plot.ICEuncrt and print.ICEuncrt
Examples
data(dulxparx)
ICEscale(dulxparx, dulx, idb, ru)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(ICEinfer)
Loading required package: lattice
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/ICEinfer/ICEscale.Rd_%03d_medium.png", width=480, height=480)
> ### Name: ICEscale
> ### Title: ICEscale() functions compute or print ICE Statistical Inference
> ### Summary Statistics relative to choice for the numerical value of the
> ### Shadow Price of Health, lambda
> ### Aliases: ICEscale
> ### Keywords: methods
>
> ### ** Examples
>
> data(dulxparx)
> ICEscale(dulxparx, dulx, idb, ru)
Incremental Cost-Effectiveness (ICE) Lambda Scaling Statistics
Specified Value of Lambda = 1
Cost and Effe Differences are both expressed in cost units
Effectiveness variable Name = idb
Cost variable Name = ru
Treatment factor Name = dulx
New treatment level is = 1 and Standard level is = 0
Observed Treatment Diff = 6.152
Std. Error of Trtm Diff = 8.186
Observed Cost Difference = -2.899
Std. Error of Cost Diff = 3.096
Observed ICE Ratio = -0.471
Statistical Shadow Price = 0.378
Power-of-Ten Shadow Price= 1
>
>
>
>
>
> dev.off()
null device
1
>