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Last data update: 2014.03.03

R: Boostrap variance of the nonparametric estimate on volumn...

NonParametric.VUS.var

R Documentation

Boostrap variance of the nonparametric estimate on volumn under ROC surface (VUS)

Description

Calculate the variance of the nonparametric estimate of volumn under ROC surface (VUS) through bootstrapping.

Usage

  NonParametric.VUS.var(x, y, z, alpha = 0.05, NBOOT = 100,FisherZ=FALSE)

Arguments

`x`	A numeric vector, a diagnostic test's measurements in the D^- (usually healthy subjects).
`y`	A numeric vector, a diagnostic test's measurements in the D^0 (usually mildly diseased subjects).
`z`	A numeric vector, a diagnostic test's measurements in the D^+ (usually severely diseased subjects).
`alpha`	A numeric value, confidence level for confidence interval, will result in (1-alpha)*100%; Default alpha=0.05, i.e., 95% confidence interval.
`NBOOT`	A numeric value, total number of bootstrap samples to draw for estimate of variance of the VUS nonparametric estimate.
`FisherZ`	A logic value. Default=FALSE. If TRUE, will transform the nonparametric estimate through Fisher's Z transformation: θ^=1/2log(frac{1+θ}{1-θ})*

Details

Return a numeric value, the variance estimation on the nonparametric VUS estimate obtained through bootstrapping.

Value

Return a list of outputs, including,

`variance`	A numeric value, the estimate of variance of nonparametric VUS through bootstrapping.
`lower`	A numeric value, the lower limit of bootstrap basic quantile confidence interval for the estimate of variance of nonparametric VUS, i.e., (alpha/2)*100% quantile. Under default alpha=0.05, lower= basic 0.25% quantile of bootstrap variance estimates of the nonparametric VUS estimator.
`upper`	A numeric value, the upper limit of bootstrap basic quantile confidence interval for the estimate of variance of nonparametric VUS, i.e., (1-alpha/2)*100% quantile. Under default alpha=0.05, upper= basic 0.975% quantile of bootstrap variance estimates of the nonparametric VUS estimator.

Warning

The bootstrap variance estimate may take a minute.

Note

Bug reports, malfunctioning, or suggestions for further improvements or contributions can be sent to Jingqin Luo <rosy@wubios.wustl.edu>.

Author(s)

Jingqin Luo

References

Bradley Efron, Robert Tibshirani, Robert J. Tibshirani (1993) An introduction to the bootstrap CRC Press.

Examples


 data(AL)
 group <- AL$group
 table(group)

 ##take the negated FACTOR1 marker measurements
 factor1 <- -AL$FACTOR1

 x <- factor1[group=="D-"]
 y <- factor1[group=="D0"]
 z <- factor1[group=="D+"]

 nonpar.vus <- NonParametric.VUS.var (x=x, y=y, z=z, alpha=0.05, NBOOT=10)

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(DiagTest3Grp)
Loading required package: car
Loading required package: KernSmooth
KernSmooth 2.23 loaded
Copyright M. P. Wand 1997-2009
Loading required package: gplots

Attaching package: 'gplots'

The following object is masked from 'package:stats':

    lowess

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/DiagTest3Grp/NonParametric.VUS.var.Rd_%03d_medium.png", width=480, height=480)
> ### Name: NonParametric.VUS.var
> ### Title: Boostrap variance of the nonparametric estimate on volumn under
> ###   ROC surface (VUS)
> ### Aliases: NonParametric.VUS.var
> ### Keywords: nonparametric htest
> 
> ### ** Examples
> 
> 
>  data(AL)
>  group <- AL$group
>  table(group)
group
D- D0 D+ 
45 44 29 
> 
>  ##take the negated FACTOR1 marker measurements
>  factor1 <- -AL$FACTOR1
> 
>  x <- factor1[group=="D-"]
>  y <- factor1[group=="D0"]
>  z <- factor1[group=="D+"]
> 
>  nonpar.vus <- NonParametric.VUS.var (x=x, y=y, z=z, alpha=0.05, NBOOT=10)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>