R: Output list object of class ICEuncrt for the High Uncertainty...

dpunc

R Documentation

Output list object of class ICEuncrt for the High Uncertainty numerical example in
the ICEinfer package, data(dulxparx).

Description

dpunc is the output list object of class ICEuncrt resulting from the following time consuming
computation: dpunc <- ICEuncrt(dulxparx, dulx, idb, ru, lambda=0.26)

Usage

data(dpunc)

Format

Output list object of class ICEuncrt.

df

Saved value of the name of the data.frame input to ICEuncrt.

lambda

Saved positive value of lambda input to ICEuncrt.

unit

Saved value of unit, cost or effe, input to ICEuncrt.

R

Saved integer value for number of bootstrap replications input to ICEuncrt.

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 included 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.

References

Obenchain RL. ICEinR.pdf Vignette-like documentation for ICEinfer
stored in the R library/ICEinfer/doc folder. 2009; 30 pages.

Examples

# Intermediate ICEinfer Output List for the dulxparx dataset...
data(dpunc)
plot(dpunc)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(ICEinfer)
Loading required package: lattice
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/ICEinfer/dpunc.Rd_%03d_medium.png", width=480, height=480)
> ### Name: dpunc
> ### Title: Output list object of class ICEuncrt for the High Uncertainty
> ### numerical example in the ICEinfer package, data(dulxparx).
> ### Aliases: dpunc
> ### Keywords: datasets
>
> ### ** Examples
>
> # Intermediate ICEinfer Output List for the dulxparx dataset...
> data(dpunc)
> plot(dpunc)
Incremental Cost-Effectiveness (ICE) Bivariate Bootstrap Uncertainty
Shadow Price = Lambda = 0.26
Bootstrap Replications, R = 25000
Effectiveness variable Name = idb
Cost variable Name = ru
Treatment factor Name = dulx
New treatment level is = 1 and Standard level is = 0
Cost and Effe Differences are both expressed in cost units
Observed Treatment Diff = 1.6
Mean Bootstrap Trtm Diff = 1.576
Observed Cost Difference = -2.899
Mean Bootstrap Cost Diff = -2.915
>
>
>
>
>
> dev.off()
null device
1
>