testve {MultNonParam}

Diagnosis for multivariate stratified Kawaguchi - Koch - Wang method

Description

Diagnostic tool that verifies the normality of the estimates of the probabilities b with the Kawaguchi - Koch - Wang method. The diagnostic method is based on a Monte Carlo method.

Usage

testve(n, m, k, nsamp = 100, delta = 0, beta = 0, disc = 0)

Arguments

n

number of observations in the first group.

m

number of observations in the second group.

k

number of strata.

nsamp

The number of estimates that will be calculated. Must be enough to be sure that the results are interpretable.

delta

Offset that depends on group.

beta

Correlation between x and y.

disc

The Mann Whitney test is designed to handle continuous data, but this method applies to discretized data; disc adjusts the discreteness.

Details

This functions serves as a diagnosis to prove that the Kawaguchi - Koch - Wang method gives Gaussian estimates for b. It generates random data sets, to which the Mann Whitney test gets applied. y is the generated response variable and x the generated covariable related to y through a regression model.

Value

Nothing is returned. A QQ plot is drawn.

References

A. Kawaguchi, G. G. Koch and X. Wang (2012), "Stratified Multivariate Mann-Whitney Estimators for the Comparison of Two Treatments with Randomization Based Covariance Adjustment", Statistics in Biopharmaceutical Research 3 (2) 217-231.

J. E. Kolassa and Y. Seifu (2013), Nonparametric Multivariate Inference on Shift Parameters, Academic Radiology 20 (7), 883-888.

Examples

testve(10,15,3,100,0.4)