DiagTest3Grp (version 1.6)

DiagTest3Grp-package: Diagnostic test summary measures for three ordinal groups

Description

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.

Details

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

References

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/.

See Also

Youden3Grp VUS

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+"]

 ## 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)