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DiagTest3Grp (version 1.6)

Diagnostic test summary measures for three ordinal groups

Description

The R package provides utilities to estimate and make inference on two summary measures for diagnostic tests when there are three ordinal groups ----volume under ROC surface (VUS) and the extended Youden index, assuming that diagnostic markers increase monotonically and stochastically with disease severity. Point estimates, 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 measures within a user-specified margin of error for future study planning.

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Version

Install

install.packages('DiagTest3Grp')

Monthly Downloads

31

Version

1.6

License

GPL (>= 2.0)

Maintainer

Jingqin Luo

Last Published

February 20th, 2014

Functions in DiagTest3Grp (1.6)

Calculate the bandwidth (normal reference rule and Sheather-Jones plug-in rule) in kernel smoothing for density estimation

DiagTest3Grp-package

Diagnostic test summary measures for three ordinal groups

Youden3Grp.Variance.Bootstrap

Obtain bootstrap variance and confidence itnerval on the extended Youden index and optimal cut-off points

print.DiagTest3Grp

Print an object of class DiagTest3Grp

Alzheimer's disease neuropsychometric marker dataset

Pairwise.DiagTest3Grp.Test

Do pairwise statistical test on the summary measure (VUS or Youden) estimate between a pair among multiple markers

NonParametric.VUS

Nonparametric estimate of volumn under ROC surface (VUS)

Volume under ROC surface (VUS) and partial VUS estimate and associated variance under normality assumptions

Obtain empirical estimation of the three correct classification probabilities

DiagTest3Grp.Test

Statistical test on the summary measure (VUS or Youden) estimate on two markers or multiple markers

The wrapper function for Youden index analysis

Draw a bootstrap sample from a given vector of data values

DiagTest3Grp-internal

Internal DiagTest3Grp functions

Calculate the variance of an estimator after Fisher's Z transformation

A wrapper function for Volume under Surface (VUS) estimate, variance estimate under normal and nonparametric assumption and sample size calculation

Fisher's Z transformation

Sample size for volume under surface (VUS)

Variance of a sample estimate for a normal standard deviation (SD) parameter

Youden3Grp.Variance.Normal

Variance estimations for the extended Youden index and associated lower and upper optimal cut-point under normality assumption

KernelSmoothing.cdf

Kernel smoothing cumulative density function (CDF)

Provide the lower and upper limit of a normal confidence interval given an estimate and its associated variance

Variance estimate of the sample estimate for a normal mean parameter

Empirical cumulative density function estimation

NonParametric.VUS.var

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

Youden3Grp.OptimalCutoff.Normal.trueMeanSD

The Youden index and optimal cut point estimation under normal distribution for three ordinal diagnostic groups

plot.DiagTest3Grp

Scatter plot and boxplot on an object of class DiagTest3Grp

SampleSize.Youden3Grp

Sample size for the extended Youden index for three ordinal groups

Youden3Grp.PointEst

Provide point estimates for the extended Youden index, the associated optimal cut-points, and sample size for three ordinal groups

Find the optimal cut-points in volumn under ROC surface (VUS) analyses