Description Usage Arguments Details Value Note Author(s) References See Also Examples
Given the diagnostic test measurements x, y, z in the three ordinal groups D^-, D^0, D^+ separately, the function repeatedly draws a bootstrap sample each of x, y, z to estimate the extended Youden index for three ordinal groups and the associated optimal cut point and obtain the final bootstrap average estimate on the Youden index and optimal cut-off point and the confidence interval.
1 2 3 | Youden3Grp.Variance.Bootstrap(x, y, z, method = "Normal", seed.seq =NULL,
randomStart.N = 5, NBOOT=10,alpha=0.05,t.minus.start = NULL,
t.plus.start = NULL, ...)
|
x |
A numeric vector, a diagnostic test's measurements for subjects in D- (usually a healthy group). |
y |
A numeric vector, a diagnostic test's measurements for subjects in D0 (usually a mildly diseased group). |
z |
A numeric vector, a diagnostic test's measurements for subjects in D+ (usually a severly diseased group). |
method |
A character argument. Specify a method to be used for estimating the extended Youden index Choices include ‘Normal’—Estimate the extended Youden index under the assumption of normal distributions of a diagnostic test in the three groups. ‘TN’—Transformed normal. Implement Box-cox transformation to approximate normality and then estimate the extended Youden index under normality. ‘EMP’—Estimate the extended Youden index by using empirical cumulative density function. ‘KS’—Estimate the extended Youden index by using Kernel density estimation with a normal reference rule for bandwidth selection. ‘KS-SJ’—Estimate the extended Youden index by using Kernel density estimation with the Sheather-Jones Plug-in method for bandwidth selection. |
seed.seq |
A numeric vector. Users can specify a sequence of random seeds for bootstrap sampling of x. Boostrapping of y and z will use seed0+1 and seed0+2. Default will be the sequence of 1:10. |
randomStart.N |
A numeric value. An argument need to be specified when the method
“EMP”, “KS” or “KS-SJ” is used to estimate the
optimal cut-point and the extended Youden index J. Default,
randomStart.N=1. See |
NBOOT |
A numeric value. Total number of bootstrapping, default=10. |
t.minus.start |
The starting points of the lower optimal
cut-point (t-) which separate the D- and D0 group. Default
t.minus.start=NULL will randomly generate starting value. See
|
t.plus.start |
A numeric value. The starting points of the upper optimal cut-point (t+) which separate the
D0 and D+ group. Default t.plus.start=NULL will randomly generate
starting value. See |
alpha |
A numeric value. the significance level, will provide the basic quantile confidence interval (alpha/2*100%,1-alpha/2*100%). |
... |
Other arguments to be passed to the R function |
This function is carried to get bootstrap estimates of the extended
Youden index and associated cut-points to provide confidence interval.
See details in Youden3Grp
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%). |
Bug reports, malfunctioning, or suggestions for further improvements or contributions can be sent to Jingqin Luo <rosy@wubios.wustl.edu>.
Jingqin Luo
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).
1 2 3 4 5 6 7 8 | x <- rnorm(50,6,1)
y <- rnorm(60,8,1.2)
z <- rnorm(40,10,1.4)
temp.res <- Youden3Grp.Variance.Bootstrap(x=x, y=y, z=z,
method="Normal",seed.seq=1:10,randomStart.N=3,NBOOT=10)
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