R: Variance estimations for the extended Youden index and...
Youden3Grp.Variance.Normal
R Documentation
Variance estimations for the extended Youden index and associated lower
and upper optimal cut-point under normality assumption
Description
Calculate the variance estimation for the extended Youden index and the
variance estimation for the associated lower
and upper optimal cut-point assuming that a diagnostic test follows
normal distributions in the three ordinal groups
(D^-,D^0,D^+).
Usage
Youden3Grp.Variance.Normal(x, y, z, alpha = 0.05)
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 D0 (usually mildly
diseased subjects).
z
A numeric vector. A diagnostic test's measurements in the D+ (usually severely
diseased subjects).
alpha
A numeric value. Significance level so that the function calculates the (1-alpha)*100% confidence interval (CI) on the estimates of
the extended Youden index and optimal cut-points under normal
assumption. Default, alpha=0.05.
Details
See details in Youden3Grp.
Value
Return a list, including the following components
var.youden
The normal-method based variance on the optimal Youden index.
var.t.minus
A numeric value.The variance on the lower optimal cut-point t.minus.
var.t.plus
A numeric value.The variance on the upper optimal cut-point t.plus.
var.youden.z
A numeric value. The variance on the Fisher's Z transformed optimal Youden index.
youden.CI
A named numeric of length 2. CI for the estimate of youden with the lower and the upper
CI limit (under the names alpha/2*100% and (1-alpha/2)*100%).
t.minus.CI
A named numeric of length 2. CI for the estimate of t.minus (the lower
optimal cut-point) with the lower and the upper
CI limit (under the names alpha/2*100% and (1-alpha/2)*100%) CI
t.plus.CI
A named numeric of length 2. CI for the estimate of t.plus (the upper
optimal cut-point) with the lower and the upper
CI limit (under the names alpha/2*100% and (1-alpha/2)*100%).
youden.z.CI
A named numeric of length 2. CI for the estimate of
Fisher-Z transformed youden with the lower and the upper
CI limit (under the names alpha/2*100% and (1-alpha/2)*100%).
partialDeriv
A numeric data frame with one row and multiple
columns, containing estimated SD parameters in each diagnosis group and the partial derivatives of Youden estimate
w.r.t the relevant mean and SD parameters which are outputted for performance
of statistical tests on markers under normal method or NA under
nonparametric method.
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
Luo, J and Xiong, C. (2012) Youden Index and Associated Optimal
Cut-point for Three Ordinal Groups. Communications In
Statistics-Simulation and Computation (in press).
See Also
Youden3GrpYouden3Grp.Variance.Bootstrap
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+"]
temp.res <- Youden3Grp.Variance.Normal(x=x, y=y, z=z, alpha=0.05)
###variance of the extended Youden index and optimal cut-points
temp.res[c("var.youden","var.t.minus","var.t.plus")]
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/Youden3Grp.Variance.Normal.Rd_%03d_medium.png", width=480, height=480)
> ### Name: Youden3Grp.Variance.Normal
> ### Title: Variance estimations for the extended Youden index and
> ### associated lower and upper optimal cut-point under normality
> ### assumption
> ### Aliases: Youden3Grp.Variance.Normal
> ### Keywords: univar 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+"]
>
>
> temp.res <- Youden3Grp.Variance.Normal(x=x, y=y, z=z, alpha=0.05)
>
> ###variance of the extended Youden index and optimal cut-points
> temp.res[c("var.youden","var.t.minus","var.t.plus")]
$var.youden
[1] 0.002232119
$var.t.minus
[1] 0.01708197
$var.t.plus
[1] 0.06095044
>
>
>
>
>
>
> dev.off()
null device
1
>