Description Details Author(s) References See Also Examples
Assuming diagnostic marker increase monotonically and stochatically with disease severity, the R package provides utilities to estimate two diagnostic test summary measures for three ordinal groups —-volume under ROC surface (VUS) and the extended Youden index. Variance, confidence interval and optimal cut-points both under the normal assumption and also the non-parametric method(s) will be provided for the summary measures. Statistical tests are implemented to compare multiple diagnostic tests and two diagnostic test. Sample size is calculated to estimate the summary measure for a diagnostic test within user-specified margin of error for future study planning.
Package: | DiagTest3Grp |
Type: | Package |
Version: | 1.0 |
Date: | 2010-10-21 |
License: | GPL-3 |
LazyLoad: | yes |
VUS
Youden3Grp
Youden3Grp.Variance.Bootstrap
SampleSize.VUS
SampleSize.Youden3Grp
Jingqin Luo, Chengjie Xiong Maintainer: Jingqin Luo <rosy@wubios.wustl.edu>
Xiong, C. and van Belle, G. and Miller, J.P. and Morris, J.C. (2006) Measuring and Estimating Diagnostic Accuracy When There Are Three Ordinal Diagnostic Groups. Statistics In Medicine 25 7 1251–1273.
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).
Jingqin Luo, Chengjie Xiong (2012). DiagTest3Grp: An R Package for Analyzing Diagnostic Tests with Three Ordinal Groups.Journal of Statistical Software, 51(3), 1-24.URL http://www.jstatsoft.org/v51/i03/.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | 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+"]
## VUS under normality assumption
normal.res <- VUS(x,y,z,method="Normal",p=0,q=0,alpha=0.05)
###S3 method
print(normal.res)
###S3 method
plot(normal.res)
##Youden index using normal method
youden.res <- Youden3Grp(x=x,y=y,z=z,method="Normal")
print(youden.res)
plot(youden.res)
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